CN117769648A

CN117769648A - Packaged goods inspection system and method thereof

Info

Publication number: CN117769648A
Application number: CN202280022336.0A
Authority: CN
Inventors: C·西蒙; W·勒加雷; S·梅塔里; A·杜迈斯
Original assignee: Simbertek Canada Ltd
Current assignee: Simbertek Canada Ltd
Priority date: 2021-01-19
Filing date: 2022-01-19
Publication date: 2024-03-26

Abstract

An inspection apparatus for inspecting a packaged cargo comprising: at least one conveyor; at least one camera for capturing box image data of each box cargo advanced through the inspection device using the at least one conveyor; and a processor configured to receive the bin image data from the at least one camera. The processor is configured to characterize a box exterior protrusion of a box cargo as a box flap in an open condition from the box image data, wherein the processor is configured to parse the box image data and determine that the box exterior protrusion is a uniform flat surface, and is programmed with a parameter array of physical characteristic parameters describing a box flap uniformity attribute that determines the uniform flat surface defining an open box flap condition.

Description

Packaged goods inspection system and method thereof

Cross Reference to Related Applications

This application is a non-provisional application of U.S. provisional patent application Ser. No. 63/287,631, filed on day 9 of 12 in 2021, and U.S. provisional patent application Ser. No. 63/138,946, filed on day 19 in 2021, the disclosures of which are incorporated herein by reference in their entireties.

Technical Field

Aspects of the disclosed embodiments relate to product inspection, and in particular to a box cargo inspection system and method thereof.

Background

There is a need for improved box cargo inspection systems and methods.

Typically, a bin load inspection system includes an LED (light emitting diode) array (curtain) illumination. The LEDs in these arrays have a considerable spacing (greater than 5 mm) between them so they only produce "sampled" images, rather than imaging the shipment entirely. Other methods use laser triangulation methods, which are fast, accurate and robust, but sensitive to reflective surfaces like shrink wrap (shrnk wrap). Some containerized cargo inspection systems employ image comparison to detect characteristics of the containerized cargo, such as open flaps (open flaps), wherein multiple images of the containerized cargo having a known/predetermined configuration are used for characteristic detection. Other packaged goods inspection systems employ laser scanners to detect characteristics of packaged goods (such as open flaps).

Drawings

The foregoing aspects and other features of the disclosed embodiments are explained in the following description, taken in connection with the accompanying drawings, wherein:

FIGS. 1, 1A, 1B and 1C are schematic illustrations of a tank inspection system in accordance with aspects of the disclosed embodiments;

FIGS. 2A and 2B are schematic illustrations of perspective views of examples of product bins verified in accordance with aspects of the disclosed embodiments;

FIG. 3 is a schematic diagram illustrating a product detection process flow diagram in accordance with aspects of the disclosed embodiments;

FIG. 4 is a diagram illustrating a general acquired image without a product as seen by a camera vision system in accordance with aspects of the disclosed embodiments;

FIG. 5 is a diagram illustrating a region of interest analyzed from the generic image illustrated in FIG. 4 in accordance with aspects of the disclosed embodiments;

FIG. 6 is a diagram illustrating one analyzed region from FIG. 5, enlarged, in accordance with aspects of the disclosed embodiments;

FIG. 7 is a schematic diagram illustrating a product measurement process flow diagram in accordance with aspects of the disclosed embodiments;

FIG. 8 is a schematic diagram illustrating in side and top views product measurements obtained by the processes of FIGS. 3 and 7 in accordance with aspects of the disclosed embodiments;

fig. 9, 9A, 9B, and 9C are schematic diagrams illustrating in side and top views real box (box) product measurements obtained by the process of fig. 3 and 7, in accordance with aspects of the disclosed embodiments;

FIG. 10 is a schematic diagram illustrating in side and top views external box product measurements obtained by the processes of FIGS. 3 and 7, in accordance with aspects of the disclosed embodiments;

FIG. 11 is a schematic diagram illustrating in side and top views a maximum bump (bulk) measurement obtained by the process of FIGS. 3 and 7 in accordance with aspects of the disclosed embodiments, and FIGS. 11A, 11B, and 11C are other schematic illustrative examples of bumps on one or more sides of a product in accordance with aspects of the disclosed embodiments;

FIG. 12 is a diagram illustrating detection of the presence of debris on a camera system window in accordance with aspects of the disclosed embodiments;

13A-13F are exemplary schematic illustrations showing a packaged cargo having open flaps in accordance with aspects of the disclosed embodiments;

FIGS. 14A-14D are exemplary schematic illustrations showing bin image data obtained using the bin inspection system of FIGS. 1 and 1A-1C, in accordance with aspects of the disclosed embodiments;

15-20 schematically illustrate example parameters employed by the bin inspection system of FIGS. 1 and 1A-1C for open flap determination in accordance with aspects of the disclosed embodiments;

FIG. 21 is a schematic illustration of the operation of the tank inspection system of FIGS. 1 and 1A-1C in accordance with aspects of the disclosed embodiments;

FIG. 22 is an exemplary flow chart of method(s) in accordance with aspects of the disclosed embodiments;

FIG. 23A is a schematic perspective illustration of image data obtained using the bin inspection system of FIGS. 1 and 1A-1C, showing bin contents having a concave (conductive) surface, in accordance with aspects of the disclosed embodiments;

FIG. 23B is an exemplary schematic illustration showing bin image data (corresponding to the concave surface of FIG. 23A) obtained with the bin inspection system of FIGS. 1 and 1A-1C, in accordance with aspects of the disclosed embodiments;

FIG. 23C is a schematic perspective illustration of a shipment having a combination of shipment characteristics that may affect shipment handling, storage, and transportation in accordance with aspects of the disclosed embodiments;

FIG. 24A is a perspective illustration of containerized cargo image data obtained using the box inspection system of FIGS. 1 and 1A-1C, showing bumps on the top surface of the containerized cargo, in accordance with aspects of the disclosed embodiments;

FIG. 24B is an exemplary schematic side illustration of shipment image data having protrusions on a bottom surface of the shipment in accordance with aspects of the disclosed embodiments;

FIGS. 25 and 25A are schematic illustrations of containerized cargo data obtained using the box inspection system of FIGS. 1 and 1A-1C, showing a side view of the containerized cargo having one or more tapers (tags) or narrowed on one or more sides of the containerized cargo, in accordance with aspects of the disclosed embodiments;

FIG. 26 is a schematic illustration of case cargo data obtained using the case inspection system of FIGS. 1 and 1A-1C showing a side view of case cargo having more than one product therein, in accordance with aspects of the disclosed embodiments;

FIG. 27 is a schematic illustration of case cargo data obtained using the case inspection system of FIGS. 1 and 1A-1C showing a side view of case cargo having one or more tapers on one or more sides of the case cargo, in accordance with aspects of the disclosed embodiments;

28A and 28B are schematic top and side illustrations of the expected box cargo dimensions according to aspects of the disclosed embodiments;

FIG. 29 is a schematic top view illustration of a plurality of palletized loads traveling generally side-by-side along a conveyor in accordance with aspects of the disclosed embodiments; and

fig. 30 is an exemplary flow chart of method(s) in accordance with aspects of the disclosed embodiments.

Detailed Description

It is noted that throughout the appended drawings, like features have like numerals. It is also noted that references herein to "top" and "bottom" qualifiers (and other space qualifiers) refer only to the orientation of the drawings as set forth in the present application, and do not imply any absolute spatial orientation.

FIG. 1 illustrates an exemplary bin load inspection system 100 in accordance with aspects of the disclosed embodiments. Although aspects of the disclosed embodiments will be described with reference to the accompanying drawings, it should be understood that aspects of the disclosed embodiments may be embodied in many forms. In addition, any suitable size, shape or type of elements or materials could be used.

One example of a box cargo(s) handled by the box cargo inspection system 100 is a shrink-wrapped product 200, the shrink-wrapped product 200 comprising product containers, or an array of one or more product containers, or product(s), included in a shrink-wrap, as illustrated in fig. 2A. Another example of a packaged good(s) is a packaged product 210 (such as a cardboard box or other suitable shipping container), as illustrated in fig. 2B, the packaged product 210 enclosing a product container, or an array of one or more product containers, or a container-less product(s) therein. The term "product" should be understood herein to include any type of consumer product(s) packaged in any type of package, such as, but not limited to, sealed cartons, tote bags, open top cartons, trays, bags and pouches with or without shrink wrap film, and the like (i.e., the term "product" and box-packed goods include shrink-wrapped products 200 and box-packed products 210). The size of the product (s)/box(s) 102 (e.g., input products) (generally referred to herein as products or packaged goods) received by the packaged goods inspection system 100 may vary greatly between different types of products. For exemplary purposes only, a typical dimension (W L H) may be between about 4in 2in (about 10cm 5 cm) and about 25in 30in (about 63cm 76 cm). Although the examples in fig. 2A and 2B are illustrated as having a generally hexahedral shape, the product(s) and/or product tank may have any desired three-dimensional shape, such as cylindrical, curvilinear, conical, oval, etc., and one or more surfaces of any side may be curved or slanted relative to another surface on the other side or the same side. As will be described in more detail below, one or more of the products 102 include a flap that can be folded to close an opening of the product container. Aspects of the disclosed embodiments provide for detection of at least the flaps, wherein the flaps are in an open or partially open configuration.

The box cargo inspection system or apparatus 100 includes at least one input conveyor 110, at least one output conveyor 120, a vision system 150, a controller 199, and a user interface 198 (see the exemplary user interface 198 outputs of fig. 8-12). The box cargo inspection system 100 forms (at least partially forms) an inbound conveyor system 195, or is otherwise included in the inbound conveyor system 195, for guiding the box cargo 102 into the logistics facility 190, wherein at least one of the conveyors 110, 120 is configured to advance the box cargo 102 into the logistics facility 190. For exemplary purposes only, the box cargo inspection system 100 communicates with at least one conveyor 110, 120 and receives box cargo 102, which box cargo 102 individually reaches the input conveyor 110 in any orientation and position, wherein the box cargo 102 is transferred from the input conveyor 110 to the output conveyor 120, as described herein. The output of the box cargo inspection system 100 includes various (quantitative) measurements that characterize each box cargo, such as a box of cargo. Examples of quantitative measurements include: "true box", "maximum protrusion", "angle of orientation", "distance from one side of the conveyor", open flaps, depressions (e.g., inward protrusions), etc.

The at least one input conveyor 110 is configured to advance the packaged goods 102 through the packaged goods inspection system 100 (also referred to herein as "packaged goods inspection apparatus 100"). For example, the at least one input conveyor 110 is one or more of a conveyor belt (e.g., a mat-top high-grip conveyor), a roller conveyor, or any other suitable product conveyance configured to transport incoming packaged goods 102 from any suitable equipment (e.g., automated or otherwise) or warehouse workers (e.g., humans). The at least one input conveyor 110 is configured to move the palletized load 102 into and through the vision system 150 with minimized vibration and slippage (e.g., the vibration and slippage is below any suitable predetermined threshold for vibration and slippage, which may depend on the resolution of the vision system 150 components). The at least one output conveyor 120 is generally similar to the at least one input conveyor 110 and transports the packaged goods 102 away from the vision system 150, 170 to any suitable destination, including suitable product handling equipment downstream of or subsequent to the packaged goods inspection system 100 in terms of processes.

Referring to fig. 1 and 1A-1C, vision system 150 is positioned (e.g., mounted) at least partially around and about conveyors 110 and/or 120 for viewing and measuring characteristics of containerized cargo 102 (as described above) propelled through containerized cargo inspection system 100 using conveyor(s) 110, 120. As described herein, the vision system 150 includes at least one camera (such as, for example, at least one sensor/imaging device 171-173) arranged to capture bin image data of each bin load 102 advanced through the bin load inspection system 100 using at least one input conveyor 110.

In accordance with aspects of the disclosed embodiments, the vision system 150 includes at least a flap detection system 170 (also referred to herein as an "imaging system" or "detection system"), the flap detection system 170 including at least one sensor/imaging device 171-173 (referred to herein as a sensor 171-173) for detecting (or otherwise enabling detection of) an open flap, a protrusion, and/or a depression of the packaged goods 102. The sensor is any suitable sensor configured to detect/sense at least flaps, protrusions, and/or depressions of the packaged goods 102, and includes, but is not limited to, cameras (only three are illustrated for exemplary purposes, and it should be understood that there may be more or less than three cameras), laser detection systems, or any other suitable optical or acoustic detection system for detecting flaps of the packaged goods 102. The sensors 171-173 may be any suitable cameras, such as, for example, three-dimensional cameras, including but not limited to time-of-flight cameras or any suitable three-dimensional imaging cameras. In one or more aspects of the disclosed embodiments, the sensors 171-173 are positioned adjacent one or more of the conveyors 110, 120 for detecting open flaps, protrusions, and/or depressions of the palletized load 102, as will be described in more detail below. As seen in fig. 1A-1C, in one or more aspects of the disclosed embodiments, the flap detection system 170 includes a laser, wherein each sensor 171-172 (only two cameras are illustrated in fig. 1A-1C for exemplary purposes, and it should be understood that more or less than two cameras may be provided) is paired with a laser 172L, 173L (note that the sensor 171 may also be paired with the laser 171L, which is not illustrated in fig. 1A-1C for brevity). The lasers 171L, 172L, 173L are configured to emit illumination patches that provide corresponding scan lines on the palletized load 102, wherein the scan lines illuminate the contours of the palletized load 102. In one or more aspects, illumination of the outline with the scan lines facilitates detection of open flaps, protrusions, and/or depressions of the palletized load 102 (e.g., by image identification of the bin image data from the sensors 172, 173). In still other aspects, one or more of the sensors 171-173 are paired with a respective laser, while the other sensor(s) 171-173 do not have an associated laser. In one or more aspects, the lasers 171L, 172L, 173L are substantially similar to the light sources 182, 183 described herein.

The vision system 150 can further include another imaging system (e.g., a contour detection system 180, also referred to as a bin inspection system or station) that is separate and distinct from the at least one sensor 171-173 of the flap detection system 170. The contour detection system 180 images the packaged cargo 102 separately and differently from the imaging of the at least one sensor 171-173 of the packaged cargo 102 for inspection of the packaged cargo in addition to the detection of the dent condition. The profile detection system 180 may be substantially similar to U.S. patent application No. 15/416,922 (and entitled "Cased Goods Inspection System and Method", now U.S. patent No. _________) filed on 1 month 26 of 2017, the disclosure of which is incorporated herein by reference in its entirety.

The contour detection system 180 includes at least one sensor/imaging device 181, 184, the sensor/imaging device 181, 184 being positioned adjacent to one or more of the conveyors 110, 120 and configured to detect/sense the top and side contours of the product 102. The at least one sensor/imaging device 181, 184 of the contour detection system 180 is configured to capture images of shadows of each tote 102 advanced through the tote inspection station 100, as described herein. The at least one sensor(s) 181, 184 of the contour detection system 180 are separate and distinct from the flap detection system 170, and the contour detection system 180 images the packaged goods 102, the imaging being separate and distinct from the at least one sensor 171-173 of the flap detection system 170, for inspection of the packaged goods 102 other than detection of open bin flaps. Here, the contour detection system 180 images the box cargo 102 for controller 199/processor 199P verification of the identity of each box cargo 102 (e.g., having a predetermined or expected identity of each box cargo) and the compliance (consistency) of each box cargo 102 with the verified (e.g., predetermined or expected) box size parameters of the box cargo 102.

In accordance with aspects of the disclosed embodiments, the profile detection system 180 includes a first light source 182, the first light source 182 emitting a first sheet of light, e.g., a continuous plane of substantially parallel/collimated light, within a small gap GP between the conveyors 110 and 120. For example, the first light source 182 may be located above the conveyors 110, 120 (as otherwise shown in fig. 1) or below the conveyors 110, 120. In one or more aspects, the first light source 182 can be common to (i.e., shared between) both the profile detection system 180 and the flap detection system 170 (e.g., the first light source can function as one of the lasers 172L, 173L as described above, or vice versa).

The profile detection system 180 further includes a first camera system 184, the first camera system 184 being positioned opposite the first light source 182, for example, with respect to the conveyors 110, 120. The first camera system 184 is positioned to receive parallel/collimated light emitted by the first light source 182 through, for example, the gap GP. For example, when the first light source 182 is located above the conveyors 110, 120, the first camera system 184 is located below the conveyors 110 and 120. In other aspects, the orientation of the first light source 182 and the first camera system 184 may be rotated about an axis defined by the direction of travel of the conveyors 110, 120, as desired, to maintain a relationship between the light source 182 (e.g., light emitter) and the camera system 184 (e.g., light receiver).

The second light source 183 emits a second sheet of light, i.e. a continuous plane of substantially parallel/collimated light, over a small gap between the conveyors 110 and 120. For example, the second light source 183 may be located on one side of the conveyor 110, 120 (the transmission of the parallel/collimated light beam of the second sheet is substantially orthogonal to the continuous plane of parallel/collimated light of the first sheet). In one or more aspects, the second light source 183 can be common to (i.e., shared between) both the profile detection system 180 and the flap detection system 170 (e.g., the second light source can function as one of the lasers 172L, 173L as described above, or vice versa).

The second camera system 181 is positioned accordingly (e.g., opposite the second light source 183) with respect to the conveyors 110, 120 to receive illumination from the second light source 183. The second camera system 181 is positioned to receive parallel/collimated light emitted by the second light source 183. For example, when the second light source 183 is located on one side of the conveyor 110, 120, the second camera system 181 is located on the other, opposite side of the conveyor 110, 120.

In accordance with one or more aspects of the disclosed embodiments, the at least one light source 182 or 183 may include a light shaper (light shaper) LS made with a lens or mirror that forms a collimated output beam. The light source is any suitable light source and may include, but is not limited to, one or more of the following: lasers, light Emitting Diodes (LEDs), gas lamps, and any other electromagnetic radiation device that is suitable for electromagnetic illumination of a target object and whose reflection or transmission may be captured by a suitable imaging system that generates an image or pseudo (pseudo) image of the illuminated target object.

The collimated output beam(s) of the light sources 182, 183 provide one or more parallel propagating light beams that, when obstructed by the packaged cargo 102, cast an orthographic projection shadow onto the input window of the corresponding camera system 184, 181 opposite the corresponding light source 182, 183. In this regard, the camera systems 184, 181 receive an incident collimated input beam output by a corresponding light source.

In the illustrated example, both camera systems 184, 181 include at least one camera 181C, 184C. The camera systems 184, 181 may also include mirrors 181M, 184M and diffusion screens 181D, 184D (referred to as diffusers in the figures). Mirrors 181M, 184M are employed, for example, to reduce the footprint of the overall case cargo inspection system by redirecting the sheet of light parallel to conveyors 110, 120. The diffusion screens 181D, 184D (which may be any suitable type of illumination diffuser) are examples of input beam shapers that spread the input beam by diffusing parallel light incident thereon from the corresponding light sources 182, 183 so that the corresponding cameras 184, 181 (e.g., camera imaging arrays having a desired predetermined width defined structurally or by any suitable controller, such as controller 199, so that the array) can capture and digitize the diffused light from the full width of the corresponding light sheet emitted by the light sources 182, 183. As can be appreciated, the camera(s) 184, 181 can image bin(s) and/or product(s) within the full width of the light sheet (as can be further appreciated, the full width can span across the lateral boundaries of the conveyors 110, 120 and the height H of the inspection system opening 101).

To reduce light footprint or to enable the use of a lower power laser-like light source with respect to the flap detection system 170 and the profile detection system 180, a smaller sheet of parallel light may be used with an overlap to maintain continuity and cover a larger surface. Any suitable calibration process may be used to realign the separate slices into a single slice by software such as controller 199.

As described herein, at least one sensor/imaging device 171-173 of the flap detection system 170 is connected to the bin inspection station 100, the sensor/imaging device 171-173 being separate and distinct from the at least one camera 181, 184. The at least one sensor/imaging device 171-173 is arranged to capture bin image data 1400 of each bin load 102 advanced through the bin inspection station 100 in addition to the bin image data captured by the at least one camera 181, 184. In the example illustrated in fig. 1 and 1A-1C, the flap detection system 170 utilizes box image data or any other suitable data from the contour detection system 180, as described in more detail herein. Here, the flap detection system 170 is located downstream relative to the product travel direction from the profile detection system 180 along the conveyor(s) 110, 120 (e.g., the product 120 passes through the profile detection system 180 before passing through the flap detection system 170); however, in other aspects, the flap detection system 170 may be located upstream from the contour detection system 180. The relative positioning of the flap detection system 170 and the contour detection system 180 is such that the flap detection system 170 images one or more exterior sides of the packaged goods 102 (in one or more aspects, all visible exterior sides are not seated against, for example, the conveyor(s) 110, 120) substantially simultaneously with the contour detection system 180 imaging the packaged goods 102, as will be described herein.

Referring to fig. 1, the flap detection system 170 includes one or more platforms, posts, or other suitable supports that are positioned adjacent to the conveyor(s) 110, 120 and upon which the sensor/imaging devices 171-173 (and in one or more aspects the lasers 171L-173L) are located. Note again that while three sensors 171-173 are illustrated in fig. 1, in other aspects, more or less than three sensors (such as, for example, the two sensors illustrated in fig. 1A-1C) may be arranged for imaging all five visible exterior sides of the palletized load 102 that are not seated against the conveyor(s) 110, 120. As the product passes through the flap detection system 170, the sensors/imaging devices 171-173 are arranged relative to the conveyors 110, 120 for imaging any suitable number of surfaces of each of the palletized loads 102; however, in other aspects, a single sensor/imaging device with appropriate prisms or mirrors may also provide images of an appropriate number of surfaces per tote 102.

In FIG. 1, the sensors 171-173 are arranged such that each sensor 171-173 images at least one or more respective exterior sides of the packaged cargo 102. For example, sensor 171 images the lateral sides (and the profiles of the longitudinal and top sides) of the box cargo 102, sensor 173 images the top (and the profiles of the lateral and longitudinal sides) of the box cargo 102, and sensor 172 is angled to image the lateral sides, top sides, and longitudinal sides of the box cargo 102. In fig. 1A-1C, the sensors 172, 173 are angled relative to each other and disposed on opposite sides of the conveyor(s) 110, 120 to image two lateral sides, two longitudinal sides, and a top of the packaged cargo 102 (e.g., the two sensors image five visible sides of the packaged cargo 102). In some aspects of the disclosed embodiments, the flap detection system is provided with any suitable illumination (e.g., such as the laser/collimated light sources described above) that facilitates imaging of the palletized load 102 moving along the conveyors 110, 120. In one aspect, the exposure (e.g., ISO and/or shutter speed) of the sensors/imaging devices 171-173 is such that the palletized load 102 moving along the conveyors 110, 120 appears to be stationary and the resulting image of the palletized load 102 moving along the conveyors is not blurred; in other aspects, the "stop motion effect" of the palletized load 102 moving along the conveyors 110, 120 may be generated by any suitable flashing illumination.

As described above, the sensors/imaging devices 171-173 are any suitable sensor/imaging devices, such as, for example, a time-of-flight camera or any other suitable imager capable of generating a three-dimensional depth map or point cloud of each tote 102 traveling along, for example, the conveyors 110, 120. In fig. 1, the sensor/imaging device 172 is positioned adjacent to the conveyors 110, 120 to image at least the leading side 102F of the box cargo 102 (e.g., the leading side 102F is the front or longitudinal side of each box cargo 102 relative to the direction of travel along the conveyors 110, 120—note that the term "front" is used herein for exemplary purposes only, and any spatial term may be used). For example, the sensor/imaging device 172 is mounted to the post 170M in any suitable manner to face in a direction generally opposite to the direction of travel along the conveyors 110, 120 in order to image the palletized load 102 traveling toward the sensor/imaging device 172. The sensor/imaging device 173 is also mounted on the post 170M and positioned above the conveyors 110, 120 to image a plan view of at least the top side 102T of the palletized load 102 traveling along the conveyors 110, 120 (e.g., the "top" side is relative to the palletized load 102 side sitting on the conveyors 110, 120—note that the term "top" is used herein for exemplary purposes only, and any spatial term may be used). The sensor/imaging device 171 is mounted on any suitable surface adjacent the conveyors 110, 120 for imaging the lateral sides 102L of the packaged goods 102 traveling along the conveyors 110, 120. Referring to fig. 1A-1C, the sensor 172 is mounted (in a manner similar to fig. 1) so as to be positioned relative to the conveyor(s) 110, 120 for imaging a perspective view of the palletized load 102, including one lateral side 102L1, a top side 102T, and a trailing or "rear" longitudinal side 102R of the palletized load 102. The sensor 173 is mounted (in a manner similar to fig. 1) so as to be positioned relative to the conveyor(s) 110, 120 for imaging a perspective view of the packaged cargo 102, including the opposite lateral side 102L2, top side 102T, and leading or front longitudinal side 102F of the packaged cargo 102. Each of the sensors/imaging devices 171-173 is positioned to produce an image of at least one respective side of the palletized load 102, and as can be appreciated, the number of cameras can depend on the particular palletized load being inspected.

As described herein, at least one camera (e.g., sensor/imaging device 171-173) is arranged to image each exposed bin side 102T, 102F, 102R, 102L1, 102L2 of each bin load 102 that is advanced through inspection apparatus 100 using at least one conveyor 110, 120 to image at least one of a bin side sag condition (or inward shift) and a bin exterior protrusion evident on each imaged bin side 102T, 102F, 102R, 102L1, 102L2 from a common image of each imaged bin side 102T, 102F, 102R, 102L1, 102L 2. The at least one sensor/imaging device 171-173 is arranged to capture bin image data 1400 of each bin load 102 advanced through the inspection apparatus 100 using the at least one conveyor 110, 120 such that the bin image data embodies at least one of a bin side recess 2300 (also referred to herein as an inward shift-see, e.g., fig. 23A) and a bin exterior protrusion 220, wherein at least one of the bin side recess 2300 and the bin exterior protrusion 220 is evident on at least one exposed bin side 102F, 102R, 102T, 102L1, 102L2, and at least one exposed bin side 102F, 102R, 102T, 102L1, 102L2 is disposed in each exposed bin side orientation of the bin load 102.

In other aspects, the at least one sensor/imaging device 171-173 is arranged to capture the bin image data 1400 of each bin load 102 advanced through the inspection apparatus 100 using the at least one conveyor 110, 120 such that the bin image data 1400 embodies a concave condition (or inwardly varying condition), wherein the concave condition is evident on the at least one exposed bin side 102T, 102L, 102F, 102R (and in some aspects, at the bottom 102B as described herein), and the at least one exposed bin side is disposed in each exposed bin side orientation of the bin load 102. In addition to or instead of the case exterior protrusion determination, at least one exposed case side 102T, 102L, 102F, 102R imaged by at least one sensor/imaging device 171-173 is arranged such that a recessed condition (which is resolved from a recessed condition apparent on the imaged at least one exposed case side 102T, 102L, 102R, 102F) extends from the at least one exposed case side 102T, 102L, 102R, 102F adjacent to the conveyor seating surface 110S, 120S on which the palletized load 102 sits.

The case cargo inspection system 100 includes any suitable controller 199 (which includes any suitable processor 199P such that references to the controller 199 performing or being configured to perform the tasks/functions described herein implies that the processor 199P operates) or any other device or system (local or remote) that includes a computer readable medium having non-transitory computer program code stored thereon that configures the controller 199 to record (register) and analyze case image data from the vision system 150 to calculate desired measurements or other suitable characteristics of the case cargo 102 (as described herein). The controller 199 is operably coupled to the at least one conveyor 110, 120 and is communicatively coupled to the at least one sensor 171-173, 181, 184 of the vision system 150 in any suitable manner, such as by any suitable wired or wireless connection, for receiving the bin image data from the at least one sensor 171-173 (see fig. 14A-14H for example bin image data 1400 from the sensor 171-173), 181, 184 (see fig. 5, 6, and 8-11 for example bin image data from the sensor 181, 184).

Note that the controller 199 (e.g., by the processor 199P) is configured such that the box cargo inspection based on the box cargo image from the contour detection system 180 is resolved separately and differently from at least one of the box side recess (also referred to as a box side recess condition) and the open box flap from the box image data 1400 (see fig. 14A-14D) from the at least one sensor 171-173 of the flap detection system 170. The controller 199 is further arranged to determine the presence of any bin-side recesses 2300 and any bin-outside protrusions 220 (see fig. 2A and 2B and fig. 9-11) of the bin load 102 from imaging data of the contour detection system 180 separate from and different from the bin image data 1400 captured by the at least one sensor 171-173 of the bin detection system 170; and resolving at least one of the bin-side recesses and bin-exterior protrusions 220 into a respective bin-side recess and open bin flap from bin image data 1400 of at least one sensor 171-173 of the flap detection system 170 that is separate and distinct from the image of the contour detection system 180. In one or more aspects, controller 199 is configured to: the presence of at least one of the bin-side recess and the bin-exterior protrusion 220 is determined from the bin image data 1400 captured by the at least one sensor 171-173 of the flap detection system 170 independent of the image of the packaged cargo 102 captured by the contour detection system 180.

In one or more aspects, controller 199 is configured to: from the box image data 1400 generated from the common image of the box cargo 102 captured by the at least one sensor 171-173 (see fig. 23B and 23C-e.g., the common image of one of the at least one sensor 171-173 or the combined image from more than one of the at least one sensor 171-173), at least one of the box side recess 2300 (see fig. 23A, as will be described below) and the box exterior protrusion 220 of the box cargo 102 is characterized as a box flap in an open condition. Here, the at least one exposed bin side 102F, 102R, 102T, 102L1, 102L2 imaged by the at least one sensor 171-173 is disposed such that at least one of the bin side recess 2300 and the bin flap in an open condition (which is resolved from at least one of the bin side recess 2300 and the bin exterior protrusion 220 apparent on the imaged at least one exposed bin side 102F, 102R, 102T, 102L1, 102L 2) extends from the at least one exposed bin side 102F, 102R, 102T, 102L1, 102L2 adjacent the conveyor seating surface 110S, 120S (fig. 1) on which the palletized load 102 sits.

When the processor is configured to characterize at least one tank top 102T or at least one tank side 102L, 102R, 102F having a dishing condition from the tank image data 1400 of the tank cargo captured by the at least one sensor 171-173, the processor 199P is programmed to resolve the predetermined planar consistency characteristics of the at least one tank top 102T or at least one tank side 102L, 102R, 102F and the tank top 102T or tank side 102L, 102R, 102F (e.g., such as from an expected tank size and a tank cargo type, e.g., stock Keeping Unit (SKU), as described herein) from the image data 1400. The processor 199P is configured to determine from the image data 1400, for each resolved inwardly varying presence, a physical characteristic describing a dishing condition of the at least one bin top 102T or the at least one bin side 102L, 102R, 102F.

Referring to fig. 3, the operation of the box cargo inspection system 100 will be described. The box cargo 102 arrives on the conveyor 110 in any orientation and position. In one or more aspects, the location of the box cargo 102 on the conveyor 110 includes a distance or gap from one side of the conveyor 110. Fig. 3 illustrates a product measurement process. The contour detection system 180 proceeds to repeat image acquisition (fig. 3, block 310) in an image cache, such as the image cache of the controller 199 processor 199P, triggered, for example, by the input conveyor encoder or alternatively by stepper motor drive circuitry (which advances at least one of the conveyors 110 and 120).

Fig. 4 illustrates a representative example, which may be referred to as an original acquired image obtained at a given encoder index value (using an imager of a camera of camera system 181, 184), such as may be generated for four light sources (e.g., as may be used in either light source 182, 183) and one camera system (e.g., camera system(s) 184, 181) implementation. The image comprises sub-areas 4GI, 4GV of illuminated and non-illuminated (non-exposed) pixels. The image analysis computer program algorithm does not take into account the complete capture area of the camera image sensor where the pixels are not exposed. Instead, consider a specific subregion 4GI, for example having a height 4H of 3 pixels and a full light sheet width 4W. Fig. 5 illustrates the considered region 5GI (such as may correspond to such a light source), which region 5GI is identified with a dashed rectangle representing the recorded image subregion 5L, processed by the image analyzer. Fig. 6 shows details of one specific region 6GI, which region 6GI is enlarged to better illustrate the region considered by the image analysis algorithm.

For each acquired image (fig. 4), the image analysis algorithm compares the pixel light intensities of pixels in the particular region 5h (fig. 5) being analyzed to normalized intensity values obtained from comparable sub-region samples (e.g., from 10 raw baseline sample images) (fig. 3, block 320). Referring to fig. 3, the normalized baseline may be a rolling baseline where at each image acquisition step 320 (where there is no potential detection, as will be described), the oldest image in the sample is deleted from the record or erased and replaced by the newly acquired original image (fig. 3, block 322). The number of images used in the baseline sample may be modified. The normalized intensity values may represent ambient illumination levels, for example accounting for changes in illumination conditions in the surrounding environment of the box cargo inspection system, as well as the presence of dust, liquid residue, or small debris on the optical receiver.

For descriptive purposes, using images acquired from the camera system 184 located below conveyors 110 and 120, controller 199 verifies (fig. 3, block 330) whether the plurality of pixels in the considered portion of the acquired image (recorded by at least one camera, or the acquired images recorded by both cameras 184, 181 if desired) have an intensity drop of more than, for example, about 40% (as compared to the normalized intensity value), and represent a width of, for example, about 30mm (about 1.2 in) or greater relative to the full width of the illumination patch captured by the acquired image. As can be appreciated, the width of the threshold width of the reduced intensity portion, referred to herein as the acquired image, can be set as desired based on environmental conditions. The reduced intensity width of the image portion corresponds to and is due to a reduction in spatial intensity caused by damage and/or obstruction or blocking of at least one portion of the input beam(s) forming the illumination patch, which damage and/or obstruction or blocking is caused, for example, by an object, which may be opaque or translucent, to pass partially through the beam/patch, for the duration of the acquired image(s). In other words, the passage of product, bin and/or packaging through the sheet produces what may also be referred to as a grayscale image for at least a portion of the acquired image width. If this is the case, the controller considers that there is a potential detection of the product or the packaged goods (FIG. 3, block 332). The threshold for intensity drop (both threshold width and threshold intensity variation) may be modified as desired (e.g., the intensity drop threshold may be about 10% drop from the standard value). As can be appreciated, the two threshold settings determine the portion of opaque or translucent material in the illumination patch that breaks down to produce a gray scale image, where such material is detectable and measurable as will be further described (and the threshold width may be about 5mm or about 0.2 in). In contrast, a completely opaque material will reflect, resulting in a substantially complete occlusion of the illumination and thus in a relevant portion of the graphic projection image.

The above process steps (e.g., fig. 3, blocks 310-332) are repeated (fig. 3, block 334) as long as a plurality of pixels given the acquired image have an intensity drop (e.g., about 40%) greater than a predetermined threshold intensity drop (which may also be represented as an absolute intensity value threshold) and represent a width of the predetermined threshold width greater than about 30mm (about 1.2 in) or greater, and the process stops when the condition is no longer true. While this first condition is true (established by exceeding two thresholds), if multiple images meeting the condition represent a potential product length of about 60mm (about 2.4 in), as may be determined by an appropriate encoder that synchronizes the capture rate, the identification conveyor displacement, and the rate (e.g., conveyor advancement rate) so as to be related to or proportional to the acquired images and/or image frames, the controller considers the containerized good 102 detected, or in other words, confirms that it is true (fig. 3, block 336) (the potential containerized good length for containerized good confirmation may be set to be greater or less, such as a displacement of about 10mm (about 0.4 in)). In this case, the controller 199 combines the following images from the two camera systems 181 and 184 (combiner 199PC (fig. 1) with processor 199P)): a previously acquired upstream image, representing, for example, a conveyor displacement of about 60mm (about 2.4 in) (a representative length may be greater or less, for example, about 10mm or about 0.4 in), in front of the detected image in which the detected palletized load 102 is disposed; wherein a plurality of images of the palletized load 102 are detected; and a subsequently acquired downstream image after the shipment 102 detection assertion representing, for example, a conveyor displacement of about 60mm (about 2.4 in), such that a composite continuous complete combined image of the shipment 102 is constructed (fig. 3, block 340) from a series of images acquired during the aforementioned duration(s) before and/or after detection) before and after the shipment 102 detection, which combined image may vary and need not be symmetrical. If the plurality of images meeting the first and second conditions (i.e., threshold and durations 330, 336) represent potential products less than, for example, about 60mm (about 2.4 in) of width/length, the controller asserts the detection (FIG. 3, block 337) as false detection or the detected packaged goods 102 are below the minimum acceptable length/width at which the image acquisition process can continue normally. The system is robust to noise or spurious signals such as falling debris.

As described above, while both conditions are asserted, the continuous construction of the combined image (or pseudo image) of scanned palletized load 102 continues beyond, for example, about 60mm (about 2.4 in) until the maximum accepted product size is reached. In other words, when the controller 199 determines that the acquired image(s) of, for example, the camera system 184 (corresponding to a desired conveyor travel, e.g., about 60mm or 2.4 in) (if there are two cameras 184, 181, such determination may be affected by the acquired image) no longer meets the above-described threshold (e.g., the considered portion of the acquired image does not have a width or intensity drop that is greater than a set threshold (e.g., about 30mm (1.2 in), about 40% drop), both), the controller 199 records the accepted bin size (such as from the recorded conveyor displacement from the encoder meeting the image acquisition exceeding the threshold). Thus, after the maximum accepted product size is exceeded, controller 199 (via appropriate programming) may continue to achieve raw image acquisition for combining into a scanned box cargo combined image for another, e.g., about 60mm (about 2.4 in). It is to be understood that the "combined image" (or pseudo-image) and "combined product image" correspond to the relative position and orientation of the illumination sources and include images of generally orthogonal sides of the palletized load, such as side view images (e.g., of the lateral side(s) 102L) and top view images (e.g., of the top side 102T).

Once, and if desired, in substantial agreement with controller 199, processor 199P constructs composite image(s) of the complete imaged palletized load, as described, controller 199 calculates a variety of quantitative measurements by the process steps illustrated in fig. 7. Referring to fig. 8, examples of quantitative measurements include: "true box", "maximum protrusion", "orientation angle", "distance from one side of the conveyor".

The "real box" measurement (fig. 7, block 710) includes the size of the best fit shape, which may be determined based on, or obtained from, the combined box cargo image. For example, the shape employed in this adaptation is a box having a length, a width and a height. Alternatively, the shape employed may be a sphere having a center and a radius. Various other shapes may be employed in the adaptation, such as, but not limited to, cylinders, ovoids, cones, and the like. Fig. 9, 9A, 9B and 9C illustrate examples of "real box" measurements (shown in fig. 9 with dashed lines on the processed images 900A, 900B, the processed images 900A, 900B representing elevation (elevation) and plan (plan) combined images, respectively) obtained from the composite images acquired/combined/constructed during inspection of the packaged goods 102, 200, 210 shown in fig. 1, 2A and 2B. As can be seen in this example, when the "true box" size is determined, any protrusions (such as protrusion 220 in fig. 2A and 2B, or protrusions not yet identified as box flaps as shown in fig. 9C) and/or protrusions 2400 seen by vision system 150 are not so identified. Here, the real box size includes a real box length RBL, a real box width RBW, and a real box height RBH. In this example, the label LAB on the box cargo 200 illustrated in fig. 2A represents the box cargo 102 and can be partially disassembled and detected in the restricted image and parsed into a best-fit shape-determined portion for omission in the occupancy assessment. However, an opaque or translucent material package, for example embodied in a composite material, is included in the actual box measurement to the extent that it conforms to the best-fit shape.

The "outer box" measurement (fig. 7, block 712) includes the dimensions of the smallest shape that contains the complete product, which can be determined based on, or obtained from, the combined product image (as can include the protrusion 220 as seen by the vision system, including the bad product (distressed product) portion, label, and package). For example, the shape employed in this fit is a box having a length, width, and height that dictate the maximum rectangular footprint of the packaged goods 102 on the conveyors 110, 120. Alternatively, the shape employed may be a sphere having a center and a radius. Various other shapes may be employed in the adaptation, such as, but not limited to, cylinders, ovoids, cones, and the like. Fig. 9A, 9B, 9C and 10 illustrate examples of "external box" measurements (shown in phantom on the processed images) obtained from images (1000A, 1000B) acquired/combined/constructed during inspection of the box cargo 102 (see also e.g., box cargo 200, 210) shown in fig. 1, 2A and 2B, which images represent the elevation/side and plane/top combined images, respectively. As can be seen in this example, when the "outer box" size is determined, any protrusions 220 and/or protrusions 2400 imaged by the vision system 150 (including such gray image projected portions that indicate translucent or opaque packaging) are considered and included. Here, the outer box dimensions include an outer box length OBL, an outer box width OBW, and an outer box height OBH. In this example, a partially disassembled label LAB (fig. 2A) on the box cargo 102 (see, e.g., box cargo 200 in fig. 2A) governs determining the footprint of the box cargo 102.

The "maximum protrusion" measurement (fig. 7, block 714) is the longest dimension obtained from the box cargo 102 being inspected. Fig. 11 illustrates a "maximum protrusion" measurement obtained from images 1100A, 1100B (using a convention similar to fig. 9, 10) acquired/combined/constructed during inspection of the box cargo 102 illustrated in fig. 1, 2A and 2B (see also e.g., box cargo 200, 210). With the product orientation determined, the "maximum protrusion" is the maximum caliper (caliper) measurement, in width, in length, and in height. As will be described herein, the bulging box cargo 102 may affect handling, storage, and palletization (palletization) characteristics of the box cargo 102 within the logistics facility 190. For example, protrusions on one or more sides of the box cargo 102 may cause unstable stacking of the box cargo, such as when palletized. Protrusions on one or more sides of the packaged goods 102 may also cause improper reorientation of the packaged goods 102, such as on a case turner (case turner) of a storage and retrieval system, where the case turner is configured to rapidly rotate or spin the packaged goods 102 to reorient the packaged goods 102. The protrusion on one or more sides of the packaged goods 102 may cause erroneous measurements of the packaged goods 102 by the automated transport vehicle 190ATV of the logistics facility 190, which may further cause missed picks, improper transfer of the packaged goods 102 to the automated transport vehicle 190ATV, and misplacement of the packaged goods. As will be described further below, the maximum protrusion may also be measured separately from the maximum caliper measurements in width, length, and height to determine the size of the protrusion relative to the adjacent edge of the palletized load 102 (see fig. 11A-11C) in order to determine whether improper handling, storage, and palletizing characteristics are present in any given palletized load 102. In one or more aspects, with respect to the width axis maximum protrusion and the length axis maximum protrusion (see fig. 11B), only the maximum protrusion on the length axis (e.g., on one lateral side 102L1, 102L2 of the box cargo) may be tracked, and only the maximum protrusion in the width direction (e.g., on one longitudinal side 102F, 102R of the box cargo 102) may be tracked. Here, the maximum protrusion in the length direction is assumed for the two lateral sides, and the maximum protrusion in the width direction is assumed for the two longitudinal sides 102F, 102R.

The product "orientation angle" is the angle of the main axis of the product relative to the direction of travel TD of the packaged cargo 102 on the conveyors 110, 120. Fig. 8 best illustrates the non-zero product "orientation angle" determined when the box is employed for the best fit (see also fig. 24, which illustrates the zero product orientation angle of the box cargo 102A and the non-zero product orientation angle of the box cargo 102B). For exemplary purposes, the "orientation angle" measurement may be the primary axis when an ovoid shape is employed in this fit.

Referring to fig. 8, the "distance to one side of the conveyor" is determined as the minimum distance obtained between the packaged cargo 102 and any one of the predetermined conveyor sides (as expressed based on the width of the light sheet, see fig. 6).

It should be understood that aspects of the disclosed embodiments are not limited to carrying out the steps illustrated in fig. 3 and 7 in the order illustrated. In one or more aspects, the determination of the measurements, as well as the condition testing, are performed in parallel, such as confirmation as the conveyors 110, 120 advance. The order of steps illustrated in fig. 3 and 7 may illustrate a hierarchical structure of an encoded logic decision network.

Once a substantial number of the above measurements are determined, the image analysis computer program of controller 199 compares the measurements (fig. 7, block 718) to the nominal values and acceptance tolerances provided (in fig. 7, block 716) to the box cargo inspection system 100. For example, a Programmable Logic Controller (PLC) (not shown) may provide at least some nominal values and acceptance tolerances for a given bin being inspected by the inspection system. Depending on user/operator preference, a "true box", "outer box" or "maximum bulge" may be considered to accept or reject the packaged cargo 102.

According to one or more aspects of the disclosed embodiments, as can be seen from the original image example illustrated in fig. 4, the recorded light intensity does not change within the acquired image. To establish a normalized baseline value of intensity as a basis or reference for comparison, an intensity value of a selectable number of non-black pixels (e.g., about 10 sample images) is considered. In one aspect, the intensity values of about 33% of the intermediate-value image (e.g., from a selected number of sample images) are considered to establish a normalized value of pixel intensity. By doing so, signal noise, light interference, etc. are eliminated in order to reduce false-box cargo detection or false measurement. The sample image, which provides a basis for determining the normalized baseline value of intensity, may be updated, refreshed on a rolling basis, as previously described, to resolve environmental changes due to environmental fluctuations, debris on the aforementioned EM source and/or vision system components, and the like.

By using the above-described procedure, the vision system 150 can automatically compensate for debris or the like existing on window panels (window panels) of the camera systems 181, 184. When this occurs, the original constructed/combined image shows a narrow line of constant pixel intensity 1200D, as shown within the stitch line 1200A in fig. 12. Upon detecting a narrow line of pixels, a warning may be sent to an operator/user of the box cargo inspection system 100 (such as through the user interface 198) to alert the need to clean the window. Here, due to the normalization of the light intensity processes described above, such debris may be gradually repositioned or removed from the combined composite image of the shipment 102 constructed by the processor 199P of the controller 199 from the image processing algorithm over several iterations (encoder steps, stepper motor steps, seconds, etc.), and thus minimizing the impact on the operation of the shipment inspection system 100.

In one aspect, the contour detection system 180 sends its decision (accept or reject) (fig. 7, blocks 720A and 720B) and the various measurements taken to, for example, the user interface 198 for subsequent use by the user/operator of the box cargo inspection system 100 (fig. 7, block 722). For example, at least conveyors 110, 120 may be operated in any suitable manner to retract or discard rejected containerized goods, and/or a lever may be actuated to transfer rejected containerized goods to any suitable "rejected product" conveyor. In other aspects, the large "orientation angle" may be reduced by actuating any suitable component of the case cargo inspection system 100 (such as a rail or other product reorienting mechanism). In still other aspects, the conveyors 110, 120 may be reversed such that the rejected bin load 102 may be rescanned. In other aspects, the contour detection system 180 sends one or more of its decisions (acceptance or rejection) and the various product measurements taken (e.g., product size, orientation, etc.) to the flap detection system 170 to facilitate flap detection, as described herein. In one or more aspects, the user interface 198 receives one or more of the above information from the contour detection system 180 and information from the flap detection system 170 (as described herein).

Referring again to fig. 1 and 1A-1C and fig. 13A-13F, the flap detection system 170 and the contour detection system 180 are configured to operate in parallel and substantially simultaneously with each other, wherein both are integrated into the box cargo inspection system 100. The flap detection system 170 is configured to detect one or more of open flaps, protrusions, and depressions that may not otherwise be detected as protrusions or box-exterior protrusions 220 by the contour detection system 180. The flap detection system 170 detects flaps (see fig. 14A-14D) having a length/size that is consistent with (e.g., corresponds to) the corresponding product/bin 102 length/size determined by, for example, the contour detection system 180 by approximating the flaps as a substantially consistent planar surface 1410. The portion or minor flap (which is only a small portion of the length of the flap) or the side of the packaged goods to which the portion or minor flap is attached may not be identified as an open flap and may be detected by the contour detection system 180 under the "true box-to-outer box" criteria described above. As will be described herein, the flap detection system 170 is configured to detect flaps, protrusions, and/or depressions on any exterior side (e.g., top, bottom, front (e.g., leading longitudinal side), rear (e.g., trailing longitudinal side), and lateral side) of any given product/bin 102, including flaps attached to the product/bin underside (e.g., the product bottom side sitting on the conveyor 110, 120).

As described above, the imaging of the exterior side of the box cargo 102 by the flap detection system 170 (as described above) is substantially simultaneous with the imaging of the exterior side of the box cargo 102 by the contour detection system 180. For example, imaging of the exterior side with the flap detection system 170 occurs substantially simultaneously with recording (by the processor 199P) of the size of the shipment from the bin image data obtained with the contour detection system 180 (see fig. 5-6), wherein the processor 199P parses the imaged shipment to the corresponding stock unit or SKU (e.g., a bin identification having a known size stored in memory accessible by the processor 199P) and identifies any bin exterior protrusions 220 as open flaps. Here, both the flap detection system 170 and the contour detection system 180 image the packaged goods 102 passing through the packaged goods inspection system 100 substantially simultaneously, wherein the time it takes the packaged goods to pass through the packaged goods inspection system 100 is on the order of about 0.1 seconds to about 0.01 seconds. For example, in one or more aspects in which the flap detection system 170 does not have laser illumination, the illumination of the packaged goods by the contour detection system 180 may be coordinated with the imaging of the flap detection system 170 such that there is a slight offset between the illumination of the packaged goods 102 by the contour detection system 180 and the imaging of the packaged goods 102 by the flap detection system 170 to avoid an illumination interface when the packaged goods 102 are imaged by the flap detection system 170; it is noted, however, that the imaging of the palletized load 102 by both the flap detection system 170 and the contour detection system 180 is substantially simultaneous for the time frame (e.g., on the order of about 0.1 seconds to about 0.01 seconds) that the palletized load 102 passes through the palletized load inspection system 100. In one or more aspects in which the flap detection system 170 includes illumination (such as from lasers 171L-173L), the illumination of the flap detection system 170 may be continuously pulsed (or periodically pulsed-e.g., turned on and off at predetermined intervals) substantially simultaneously with the illumination of the packaged goods 102 by the contour detection system 180 such that the imaging of the packaged goods 102 by both the flap detection system 170 and the contour detection system 180 is substantially simultaneous. It is noted that in one or more aspects, one or more of the lasers 171L-173L have a fixed or predetermined orientation such that the scanning/imaging of the palletized load 102 by the flap detection system 170 is affected by the palletized load movement along the conveyor(s) 110, 120; although in other aspects one or more of the lasers 171L-173L are movable relative to the conveyor(s) 110, 120 such that scanning/imaging of the palletized load 102 by the flap detection system 170 is effected by movement of the one or more lasers 171L-173L and is independent of (or decoupled from) palletized load movement along the conveyor(s) 110, 120.

As described herein, the contour verification system 180 analyzes the bin verification characteristics of the packaged cargo 102 described above, wherein at least a portion of the open flap detection, the recess detection, and the projection detection are performed by the flap detection system 170. Similarly, the flap detection system 170 resolves at least one portion of open flap detection, concave detection, and convex detection, wherein the bin inspection characteristics are resolved by the contour inspection system 180. As will be described below, the controller 199/processor 199P is configured to, upon validation (i.e., from the image data obtained from the contour inspection system 180), have the desired bin shape for the respective bin load 102; the controller 199/processor 199P determines from the other image data (i.e., from the flap detection system 170) the compliance of the respective packaged goods 102 with the predetermined bin form fit characteristics for handling, storage, and palletization of the packaged goods 102 within the logistics facility 190. As will be described in greater detail herein, the predetermined bin form fit characteristics inform of the fit acceptance of the respective bin load 102 within a predetermined fit space or location of the logistics facility 190 (e.g., storage space or other holding location of the storage array 190SA, payload bins of the automated transport vehicle 190ATV, pallet load build locations in a pallet build formed in the logistics facility 190, etc.). As described herein, in one or more aspects, the predetermined bin form fit characteristic is an inward protrusion or depression of at least one side 102T, 102L, 102F, 102R of the bin shape of the respective bin load relative to the flat bin side.

In one or more aspects, the case cargo contour inspection and the open flap detection (including the concave detection and the convex detection) can be implemented independently of each other but substantially simultaneously. For example, the contour verification system 180 is not obstructed by open flap conditions, depressions, and/or protrusions of the packaged goods 102, and the box verification characteristics (for packaged goods meeting the contour verification system 180 verification criteria) are resolved independent of the shielding of the open flap, depression, and/or protrusion shielding/box exterior side pair of the sensors 171-173 of the fold detection system 170.

Although the flap detection system 170 may be initialized from the contour verification system 180-the contour verification system 180 resolves the box exterior protrusions 220 (fig. 2A and 2B) of the packaged goods 102 that are acceptable for/pass the contour verification criteria (i.e., boxes that do not meet the packaged goods contour verification criteria are rejected in any suitable manner, such as by transfer to a reject conveyor, removal by trained personnel, etc., as described herein), the open flap, protrusion, and depression determinations are made by the flap detection system 170. While the bulge on the sides of the packaged goods 102 may be determined by both the flap detection system 170 and the profile detection system 180, the flap detection system 170 may provide more details regarding the bulge of the box handling (e.g., by an automated transport vehicle 190ATV, a pallet stacker (pallet) 190P, etc.) and box placement within the logistics facility 190 (fig. 1) (e.g., on a pallet, in a storage array 190SA, etc.), the packaged goods inspection system 100 is part of the logistics facility 190. Suitable examples of storage and retrieval systems in which aspects of the disclosed embodiments may be deployed include, but are not limited to, those described in the following patents: U.S. patent No. 10800606 (entitled "Material-Handling System Using Autonomous Transfer and Transport Vehicles") issued 13 in 10 months 2020, U.S. patent No. 10556743 (entitled "Storage and Retrieval System") issued 11 in 2 months 2020, U.S. patent No. 10633184 (entitled "Replenishment and Order Fulfillment System") issued 28 in 4 months 2020, U.S. patent No. 9475649 (entitled "Pickface Builder for Storage and Retrieval Systems") issued 25 in 10 months 2016, U.S. patent No. 10106322 (entitled "Bot Payload Alignment and Sensing") issued 23 in 2 months 2018, U.S. patent No. 10703585 (entitled "Pallet Building System") issued 7 in 7 months 2020, and U.S. patent No. 10781060 (entitled "Storage and Retrieval System Transport Vehicle") issued 22 in 9 months 2020, the disclosures of which are incorporated herein by reference in their entirety.

As an example, with respect to the detection of an open flap condition, for a packaged cargo 102 that is acceptable to the contour verification system 180, and with the determined box exterior protrusion 220 (i.e., determined from the contour verification system 180), the controller 199 initiates imaging of the packaged cargo 102 with the sensors 171-173 of the flap detection system 170. When the flap detection system 170 determines the box exterior protrusion 220 as an open flap, the controller 199 records the open flap condition in any suitable memory/database (note that the box cargo 102 remains accepted by the contour inspection system 180) using the identity of the box cargo 102 (e.g., the box cargo identification number shown in tables 1 and 2 as described herein) for disposal of the box cargo 102 by any suitable box cargo disposal device (e.g., the pallet stacker 190P, robotic arm, automated transport vehicle 190ATV, etc.). When the flap detection system 170 determines that the box exterior protrusion 220 is not an open flap, the controller 199 may not process the box image data 1400 (see fig. 14A-14H for exemplary image data) from the sensors 171-173 of the flap detection system 170. In one or more aspects, when the contour inspection system 180 does not detect the box exterior protrusion 220, the controller 199 may initialize the flap detection system 170 for the sensors 171-173 to image the packaged goods 102 substantially simultaneously with the inspection of the packaged goods 102 by the contour inspection system 180, wherein the flap detection system 170 images sides of the packaged goods 102 to detect the exterior protrusion(s) apparent on each (or one or more) visible sides of the packaged goods to verify the discovery of the contour inspection system as to the presence or absence of the box exterior protrusion 220 (note that the packaged goods remain accepted by the contour inspection system 180).

As described herein, the flap detection system 170 is configured to image all (five) visible/unsettled sides (i.e., five sides that are not seated on the conveyors 110, 120 and visible to the sensors 171-173) of the packaged goods 102 (with the at least one sensor 171-173). The at least one sensor 171-173 is arranged to image each exposed bin side 102T, 102L, 102R, 102F of each bin load 102 advanced through the bin load inspection system 100 using the at least one conveyor 110, 120 to image a bin exterior protrusion 220 apparent on each imaged exposed bin side 102T, 102L, 102R, 102F. In one or more aspects, the bin image data 1400 (see fig. 14A-14H for exemplary image data) captured by the sensors 171-173 of each of the bin cargos 102 embodies each of the exposed bin sides 102T, 102L, 102R, 102F of the respective bin exterior 102E (fig. 1). In one or more aspects, the box image data 1400 embodies the box exterior protrusion 220, wherein the box exterior protrusion 220 is evident on at least one exposed box side 102T, 102L, 102R, 102F, and the at least one exposed box side 102T, 102L, 102R, 102F is disposed in each exposed box side orientation of the packaged good 102 (e.g., the box image data 1400 identifies the side on which the open flap is detected and/or the orientation of the open flap). In one or more aspects, the imaged exposed bin sides 102T, 102L, 102R, 102F are disposed such that an open bin flap 1300 (see fig. 13A-13F) resolved from a bin exterior protrusion 220 apparent on the imaged exposed bin sides 102T, 102L, 102R, 102F extends from the exposed bin sides 102T, 102L, 102R, 102F adjacent to a conveyor seating surface CSS (see fig. 13E) on which the palletized load 102 sits.

Fig. 13A-13F illustrate an exemplary open flap configuration in which the flap detection system 170 is configured to detect. Fig. 13A illustrates a lateral side view of the packaged cargo 102 with the leading edge flap 1300TA attached to (e.g., hinged to) the edge of the top 102T partially opened at an angle a (open). The angle α is illustrated herein as an acute angle, but may be any angle ranging from about 1 ° to about 270 °. Fig. 13B is a lateral side view of the box cargo 102 with the flap 1300TA at or otherwise hinged to the leading edge of the top 102T open at an angle α and the flap 1300TV at or otherwise hinged to the trailing edge of the top 102T open at about 90 ° relative to the top 102T. Fig. 13C is a lateral side view of the packaged cargo 102 with the flap 1300FA at or otherwise hinged at the leading edge of the top 102T being inclined at an angle β and the flap 1300RH at or otherwise hinged at the trailing edge of the top 102T being inclined at an angle θ or about 180 °. Here, the angle β is illustrated as a reflex angle, and the angle θ is illustrated as about 180 °; however, in other aspects, the angles β, θ may each be in the range from about 1 ° to about 270 °. Fig. 13D is a lateral side view of the packaged cargo 102 with both the leading and trailing edge flaps 1300TA1, 1300TA2 tilted relative to the top at respective angles α1, α2, wherein the respective angles may range from 1 ° to about 270 °. Fig. 13E is a lateral side view of the packaged cargo 102 with flap 1300BA hinged at the leading edge of the bottom 102B of the packaged cargo 102 open at an angle β2 relative to the bottom 102B and flap 1300BR hinged at the trailing edge of the bottom 102B of the packaged cargo 102 open at an angle θ2 of about 180 ° relative to the bottom. Here, the angle β2 is illustrated as a reflex angle, and the angle θ2 is illustrated as about 180 °; however, in other aspects, the angles β, θ may each be in the range from about 1 ° to about 270 °. Fig. 13F is a plan view of the top 102T of the packaged cargo 102 with the flaps 1300VR on the lateral side edges of the rear or trailing side 102R of the packaged cargo 102 open at an angle a 3 relative to the rear side 102R. The angle α3 is illustrated here as an acute angle, but may be any angle ranging from about 1 ° to about 270 °. As described above, fig. 130A-130F are non-limiting illustrative examples of flap orientations that the flap detection system 170 is configured to detect. As can be appreciated, the products 102 illustrated in fig. 13A-13D can have any orientation on the conveyors 120, 110 such that the hinged sides of the flaps extend in a generally transverse direction relative to the conveyors 120, 110 or in a generally longitudinal direction relative to the orientation of the conveyors 120, 110 (i.e., along the direction of travel of the conveyors), or have any other orientation therebetween.

Still referring to fig. 1 and also to fig. 13A-13F and 14A-14H, and as described above, the flap detection system 170 includes at least one sensor/imaging device 171-173, the sensor/imaging device 171-173 being arranged to capture product/bin image data 1400 (see fig. 14A-14H for exemplary image data) of each of the palletized loads or products 102 advanced by the conveyors 110, 120 by the at least one sensor/imaging device 171-173. At least one sensor/imaging device 171-173 captures image data 1400 having any suitable resolution to enable open flap determination, as described herein. For exemplary purposes only, the image resolution provided by the at least one sensor/imaging device is about 3mm (about 0.1 in) in the X-direction (e.g., a direction generally parallel to the product flow along the conveyors 110, 120), about 1.5mm (about 0.05 in) in the Y-direction (e.g., a direction generally perpendicular to the product flow along the conveyors 110, 120 in a plane defined by the product support surfaces of the conveyors 110, 120), and about 1.5mm (about 0.05 in) in the Z-direction (e.g., a direction generally perpendicular to the product support surface CSS of the conveyors 110, 120). In other aspects, the resolution in one or more of the X, Y, Z directions can be greater or less than the resolution described above.

As described above, the controller 199 (including its processor 199P) is coupled to the conveyors 110, 120 and is communicatively coupled to the at least one sensor/imaging device 171-173 to receive the bin image data 1400 from the at least one sensor/imaging device 171-173. Here, triggering of at least one sensor/imaging device 171-173 is accomplished in the manner described above, such as by the contour detection system 180, or in a manner substantially similar to that described above with respect to the contour detection system 180. In one or more aspects, the flap detection system 170 proceeds to one or more image acquisitions in an image cache, such as the image cache of the controller 199 processor 199P, where the image acquisitions are triggered by the conveyor encoder or alternatively by stepper motor drive circuitry (which advances at least one of the conveyors 110, 120). In other aspects, image acquisition may be implemented in any suitable manner (such as with a motion sensor, etc.).

As will be described herein, the controller 199 (e.g., by any suitable non-transitory computer program code) is configured to characterize the box exterior protrusion 220 (see fig. 2A and 2B) of the box cargo 102 from the box image data 1400 as flaps 1300TA, 1300TA1, 1300TA2, 1300TV, 1300FA, 1300RH, 1300BA, 1300BR, 1300VR (commonly referred to as flaps or box flaps 1300) in an open condition (see, e.g., fig. 13A-13F) (e.g., open box flaps). Controller 199 (via processor 199P) is configured to parse box image data 1400 and determine that box exterior protrusion 220 is a uniform flat surface 1410. Processor 199P is programmed with a parameter array 199A (fig. 1-also referred to herein as parameter array 199A) of physical characteristic parameters that describe a flap uniformity attribute that determines a uniform planar surface 1410 that defines an open flap condition. The processor 199P is configured to generate (e.g., using any suitable computer program code to implement its generation) a physical characteristics array 199C from the box image data 1400 for each determined uniform flat surface 1410, and apply a parameter array 199A to the physical characteristics array 199C to resolve the uniform flat surface 1410 into open box flaps, such as illustrated in fig. 13A-13F and 14A-14H. The set of physical characteristics 199C describes the uniform flat surface as a box flap herein and determines that the box flap is in an open flap condition based on the set of parameters 199A of physical characteristics.

The processor 199P is configured to parse the bin image data 1400 (in addition to or instead of parsing the open bin flap condition) and determine that at least one bin top 102T or at least one bin side 102L, 102R, 102F has an inward variation (i.e., a depression). Processor 199P is programmed with a parameter array 199A of physical characteristic parameters that describe an inwardly varying attribute that determines an inwardly variation that defines a dishing condition. The processor 199P is configured to generate a physical characteristics array 199C from the bin image data 1400 for each determined inward variation, and apply a parameter array 199A to the physical characteristics array 199C to resolve the inward variation to a dishing condition. While the parameter array 199A and the physical characteristic array 199C are described as including both open flap and recess characteristics, in other aspects, separate parameter and physical characteristic arrays may exist for each of the open flap and recess characteristics.

A parameter array 199A of physical characteristic parameters (also referred to herein as parameter array 199a—see fig. 1) is programmed into the controller 199 and accessible to the processor 199P. The parameter array 199A of physical characteristic parameters describes one or more box flap uniformity attributes or characteristics of a uniform plane that determine and describe uniformity of the plane (e.g., uniform planar surface 1410) with respect to, for example, the size of the packaged goods (length, width, and height of the corresponding packaged goods received by the controller 199 from the profile detection system 180). The conforming planar surface 1410 defines an open box flap condition and includes any suitable physical characteristics for a given shipping container cargo/product configuration and/or flap configuration. The conforming plane or flat surface 1410 is dependent on the physical characteristics and is resolved by any suitable image processing by the controller 199, wherein the controller 199 determines (e.g., from one or more of the contour detection system 180 and the flap detection system 170) whether the outside-box protrusion 220 (fig. 2A and 2B) is present, and then determines whether the outside-box protrusion is a conforming plane based on the physical characteristics of the conforming plane. For example, processing of the image data from the flap detection system 170 determines whether the consistent plane converges to define an edge having at least one of the box sides (e.g., top, lateral sides, and longitudinal sides). When it is determined that there is an edge with at least one of the box sides and the physical characteristics or parameters in the set of physical characteristics 199C are met, the controller 199 determines that an open flap is present and records the open flap with the identity of the respective packaged cargo 102 for further processing of the respective packaged cargo 102.

In the examples provided herein, the physical characteristics or parameters in the physical characteristics array 199C include five parameters (as described below), but it should be understood that in other aspects, there may be more or less than five parameters employed for the determination of the open flap condition. These parameters are applied to each of the visible sides (e.g., top 102T, longitudinal sides 102, 102R, and lateral sides 102L) of the packaged goods 102 for determination of an open flap condition on each side, wherein the record of the open flap condition may pertain not only to the identity of the respective packaged goods, but also to the side of the respective packaged goods on which the open flap is present. Knowing on which side the open flap is present may facilitate further processing of the respective packaged goods by the automated equipment or determining rejection of the packaged goods.

It is noted that the physical characteristics in parameter array 199A and physical characteristics array 199C are container cargo 102 characteristics that are different than those of container cargo 102 imaged by profile detection system 180 (as described above). For example, referring also to fig. 15-20, parameter array 199A and physical characteristics array 199C each include, but are not limited to, five threshold parameters (again more or less than five may be employed) that are:

Minimum opening angle of the flaps (e.g., minimum angle alpha from the horizontal edge of the packaged goods 102) _MH And a minimum angle alpha from the vertical edge of the box cargo 102 _Mv See figures 15 and 16),

the minimum flap depth MFD relative to the base of the flap (e.g., the distance from the hinge side HS of the flap or the base to the opposite free side FS of the flap-see fig. 18), this parameter may be expressed in some aspects as a ratio,

the ratio of the minimum flap length MFL to the product box length PBL (e.g., MFL/PBL) (see figure 17),

the minimum product box length (or width) L added by the flaps (e.g., L is the total length MPBLF of the product with the open flaps 1300 minus the product box length PBL-see fig. 19), note that the minimum product box length (or width) is the minimum angle a from the horizontal edge of the packaged goods 102 _MH And/or a minimum angle alpha from the vertical edge of the packaged cargo 102 _Mv Is a function of (2)

The minimum product box height BH added by the flaps (e.g., BH is the total height MPBHF of the product with the open flaps 1300 minus the product box height PBH-see fig. 20), note that the minimum product box height is the minimum angle α from the horizontal edge of the packaged cargo 102 _MH And/or a minimum angle alpha from the vertical edge of the packaged cargo 102 _MV Is a function of (2).

The detection system 170 is configured to reject the containerized good 102 when one or more of these parameters/thresholds are exceeded. In one or more aspects, the flap detection system 170 is configured to reject the packaged goods 102 when each or all of the following are exceeded: minimum opening angle alpha of folded plate _MH 、α _MV The method comprises the steps of carrying out a first treatment on the surface of the Minimum flap depth MFD; the ratio of the minimum flap length MFL to the product box length PBL; and a minimum product box length (or width) MPBLF (or a minimum product box height MPBHF increased by the flaps) increased by the flaps, depending on whether the flaps are on the vertical or horizontal sides of the product. In still other aspects, the flap detection system 170 is configured to reject the packaged goods 102 when each or all of the following are exceeded: minimum opening angle alpha of folded plate _MH 、α _MV The method comprises the steps of carrying out a first treatment on the surface of the Minimum flap depth MFD; the ratio of the minimum flap length MFL to the product box length PBL; and a minimum product box length (or width) MPBLF (MPBLF at minimum opening angle alpha) increased by the flaps _MH 、α _MV Provided for), minimum product box height MPBHF increased by flaps (MPBHF at minimum opening angle alpha) _MH 、α _MV As a condition). Rejected box cargo 102 may be routed off of the conveyor and/or an operator may be notified of the rejection via user interface 198 in a manner generally similar to that described above with respect to contour detection system 180.

For exemplary purposes only, the minimum opening angle alpha of the flap _MH 、α _MV Is 15 deg., the minimum flap depth MFD is about 20mm (about 0.7 in), the ratio of the minimum flap length MFL to the product box length PBL is about 50%, the minimum product box length (or width) MPBLF added by the flaps is about 20mm (about 0.7 in), and the minimum product box height MPBHF added by the flaps is about 20mm (about 0.7 in). In other aspects, the minimum opening angle alpha of the flap _MH 、α _MV The minimum values of minimum flap depth MFD, the ratio of minimum flap length MFL to product box length PBL, minimum product box length (or width) MPBLF increased by the flaps, and minimum product box height MPBHF increased by the flaps may be greater or less than the above.

As described herein, the flap detection system 170 and the contour detection system 180 operate in parallel, with at least some information (box image data) shared between the systems. For example, to determine whether at least some of the above parameters are exceeded, the contour detection system 180 sends information regarding the physical characteristics of any given bin (e.g., length, width, height, orientation on the conveyors 110, 120, and in some aspects, whether the bin exterior protrusion 220 is present) to the flap detection system 170 so that the flap detection system 170 determines whether the parameters/thresholds are exceeded. For example, referring to fig. 1 and 21, in operation, the flow of products 102P1, 102P2, 102P3 moves along the conveyors 110, 120 through the contour detection system 180 and the flap detection system 170. As each of the shipment 102P1, 102P2, 102P3 passes through the contour detection system 180, the contour detection system 180 detects a product characteristic (e.g., length, width, height, protrusion, orientation, etc., on the conveyor, as described herein) of each of these shipment 102P1, 102P2, 102P3 and sends at least some of the detected information to the flap detection system 170. For example, the flap detection system 170 may employ the length, width, height, and orientation of each respective packaged cargo 102P1, 102P2, 102P3 in combination with the image data 1400 captured by the flap detection system 170 for determining the presence of open flaps. The flap detection system 170 may also employ any detection of the protrusions by the contour detection system 180 to identify areas of interest for the respective packaged goods 102P1, 102P2, 102P3 where the open flaps may be present.

Referring also to fig. 14A-14H, in one or more aspects, the physical characteristics obtained by the flap detection system 170 from the contour detection system 180 are compared to the image data captured by the flap detection system 170, for example, to confirm or verify the location of each product in the product stream (e.g., the products pass through the flap detection system 170 in the same order as the products pass through the contour detection system 180), and to determine whether the products that have passed through the contour detection system 180 are suitable for storage, disposal, and palletization in the logistics facility 190 (fig. 1). The physical characteristics obtained by the contour detection system 180 may also be employed by the flap detection system 170 to verify at least some of the physical characteristics of the products 102P1, 102P2, 102P3, as determined by the flap detection system 170 from the image data 1400.

Referring to fig. 14A, an example of image data 1400 captured by the flap detection system 170 is illustrated. For illustrative purposes, the image data 1400 illustrated in fig. 14A is a plan or top view of the palletized load 102P 1. Here, the image data is point cloud data, but may be any suitable image data that enables image analysis for detecting characteristics of the packaged goods/products. In this example, the flap detection system 170 determines (by any suitable image processing algorithm/procedure) that the protrusions or box-exterior protrusions 1450, 1451 (which may have been identified by the contour detection system 180 as box-exterior protrusions, but are not identified as open flaps) are uniform planar surfaces 1410 and identifies these box-exterior protrusions 1450, 1451 as open flaps 1300A, 1300B. The flap detection system 170 is based on a graph Like data 1400, to construct a physical characteristics array 199C (see FIG. 1, tables 1, 2 below) of the shipment 102P1, wherein the physical characteristics array 199C includes, for example, a flap angle α _vD (from the vertical side of the product) and flap length L _D (from the vertical side). Controller 199 compares the data in physical characteristics array 199C to corresponding data in parameter array 199A to determine if any threshold/parameter in parameter array 199A has been exceeded. For example, in fig. 14A, flap angle α _vD Possibly greater than the minimum angle alpha _Mv While the length L of the flaps 1300A, 1300B _D Less than the length L. Here, based on at least these two parameters when compared to the corresponding values of parameter array 199A (and insight that the packaged goods are rejected if more than one of the following is exceeded: minimum opening angle of flap alpha _MH 、α _MV The method comprises the steps of carrying out a first treatment on the surface of the Minimum flap depth MFD; the ratio of the minimum flap length MFL to the product box length PBL; a minimum product box length (or width) L increased by the flaps; and a minimum product box height BH increased by the flaps), the shipment 102P1 is acceptable and not rejected (e.g., depending on whether other parameters are exceeded, and/or how many parameters and which parameters are considered in the rejection determination).

Fig. 14B is another exemplary illustration of image data 1400 captured by the flap detection system 170. For illustrative purposes, the image data 1400 illustrated in fig. 14B is a lateral side view of the palletized load 102P 2. Here, the image data is point cloud data, but may be any suitable image data that enables image analysis for detecting product features. In this example, the flap detection system 170 determines (by any suitable image processing algorithm/procedure) that the protrusion or box exterior protrusion 1452 (which may have been identified by the contour detection system 180 as box exterior protrusion 220, but is not identified as an open flap) is a consistent planar surface 1410 and identifies the box exterior protrusion 1452 as an open flap 1300 (e.g., an open flap hinged to the bottom side 102B of the packaged cargo 102P 2). The flap detection system 170 constructs a physical characteristics array 199C (fig. 1) of the packaged goods 102P2 based on the image data 1400, wherein the physical characteristics array 199C comprises at leastLength of folded plate L _D And a folded plate angle alpha _vD . For example, in FIG. 14B, flap angle α _vD Possibly greater than the minimum angle alpha _Mv While the length L of flap 1300 _D Possibly of length L. Here, based on at least these two parameters when compared to the corresponding values of parameter array 199A (and insight that the packaged goods are rejected if more than one of the following is exceeded: minimum opening angle of flap alpha _MH 、α _MV The method comprises the steps of carrying out a first treatment on the surface of the Minimum flap depth MFD; the ratio of the minimum flap length MFL to the product box length PBL; a minimum product box length (or width) L increased by the flaps; and a minimum product box height BH increased by the flaps), the shipment 102P2 may be rejected (e.g., depending on whether other parameters are exceeded, and/or how many parameters and which parameters are considered in the rejection determination).

Fig. 14C is another exemplary illustration of image data 1400 captured by the flap detection system 170. For illustrative purposes, the image data 1400 illustrated in fig. 14B is a front (or back/rear) side view of the palletized load 102P 3. Here, the image data is point cloud data, but may be any suitable image data that enables image analysis for detecting characteristics of the packaged goods/products. In this example, the flap detection system 170 determines (by any suitable image processing algorithm/procedure) that the protrusions or bin exterior protrusions 1453, 1454 (which may have been identified by the contour detection system 180 as bin exterior protrusions, but are not identified as open flaps) are a consistent planar surface 1410 and identifies the bin exterior protrusions 1453, 1454 as open flaps 1300A, 1300B (e.g., open flaps hinged to the top side 102T of the packaged goods 102P 3). The flap detection system 170 constructs a physical property array 199C (fig. 1) of the packaged goods 102P3 based on the image data 1400, wherein the physical property array 199C includes at least a flap height BH _D And a folded plate angle alpha _HD . For example, in fig. 14C, flap angle α of flap 1300A _HD Possibly smaller than the minimum angle alpha _MH Flap angle α of flap 1300B _HD Possibly greater than the minimum angle alpha _MH The height of flap 1300A is less than height BH, and the height BH of flap 1300B _D Greater than the height BH. For example, here, based on at least the parameters of flap 1300B when compared to the corresponding values of parameter array 199A (and insight that the packaged goods are rejected if more than one of the minimum opening angle alpha of the flaps is exceeded _MH 、α _MV The method comprises the steps of carrying out a first treatment on the surface of the Minimum flap depth MFD; the ratio of the minimum flap length MFL to the product box length PBL; a minimum product box length (or width) L increased by the flaps; and a minimum product box height BH increased by the flaps), the shipment 102P2 may be rejected (e.g., depending on whether other parameters are exceeded, and/or how many parameters and which parameters are considered in the rejection determination).

Fig. 23A-23C are other exemplary illustrations of image data 1400 captured by the flap detection system 170. For illustrative purposes, the image data 1400 illustrated in fig. 23A is a front (or back/rear) perspective view of the box cargo 102, with the box side recess 2300 present, for example, on top of the box cargo 102 (note that the box side recess may be present on any visible side of the box cargo 102 for detection by the flap detection system 170). Here, the image data 1400 is photographic image data of the packaged goods 102, but may be any suitable image data that enables image analysis for detecting packaged goods/product characteristics. Fig. 23B illustrates image data 1400 of the packaged cargo 102 of fig. 23A as point cloud data.

In this example, the flap detection system 170 determines the presence of the box-side notch 2300 by analyzing one or more sides of the packaged goods 102 (by any suitable image processing algorithm) and if the box-side notch 2300 is present, the flap detection system 170 determines the depth of the notch 2300. As an example, the flap detection system 170 determines the presence of the box-side recess 2300 (e.g., in a manner generally opposite to that described above with respect to the box-exterior protrusion 220) by determining that one or more box sides fail to describe a consistent planar surface (i.e., that no consistent planar surface exists on one or more sides) within a predetermined planar surface threshold criteria (e.g., based on a three-dimensional analysis of the box-packaged cargo 102). For example, the absence of a uniform flat surface (or the presence of a non-uniform surface) on one side of the box cargo 102 may be determined by detecting one or more apertures 2310 that may be formed by, for example, the box flap 1300. When the box side recess 2300 is on the side of the packaged cargo 102 that is free of flaps (or has flaps but is not separated to form apertures 2310 therebetween), the absence of a uniform planar surface may be determined by the flap detection system 170 by determining the presence of one or more of the recesses 2340, corrugations 2320, and apertures (perforations) 2330 on the side of the packaged cargo 102 (e.g., based on a three-dimensional analysis of the packaged cargo 102). The tank side recess 2300 may be formed in any suitable area of the side of the packaged cargo 102. For example, the tank side recess may be generally in the middle of the side (see, e.g., recess 2340, aperture 2330, and tank side recess 2300), at the edges of the side (see, e.g., crease 2320 and tank side recess 2300), and/or extend across the side to transition from the edges to the middle of the side (or beyond the side) (see, e.g., crease 2320 and tank side recess 2300).

For exemplary purposes only, if the length-wise dimension (e.g., with respect to the box cargo length, width, and/or height), width-wise dimension (e.g., with respect to the box cargo length, width, and/or height), or the diameter of aperture 2310 (e.g., formed by flap 1300) is greater than about 2 inches, then the box-side recess is determined (in other aspects, the criteria for determining the box-side recess may be more than about 2 inches or less than about 2 inches). Similar appropriate criteria are applied to the determination of the tank side recess 2300 based on the recess 2340, the crease 2320, and the small hole (perforation) 2330.

When a bin side recess 2300 is present, the flap detection system 170 determines a depth 2399 of the non-uniform surface (e.g., depression, recess, crease, etc.), wherein the depth 2399 is measured from, for example, a bin load edge 2323 formed by the side of the bin load on which the non-uniform surface is present and the adjacent side of the bin load (where the depth 2399 is measured from an edge formed by the top 102T of the bin load and one or more vertical sides (e.g., lateral sides 102L and/or longitudinal sides 102F, 102R) -see also fig. 11A). In other aspects, the depth 2399 may be measured from any other suitable reference point of the box cargo, such as the bottom or the opposite side with respect to the side on which the non-uniform surface is present.

Here, if the depth 2399 of the non-conforming surface is greater than a predetermined threshold, such as, for example, about 1 inch (about 25 mm), then the box cargo 102 is classified as unsuitable (i.e., rejected as not conforming to the corresponding predetermined box form fit characteristics) for box handling, storage, and palletization within the logistics facility 190, and is removed from automated handling within the logistics facility 190 in the manner described above. In addition to or instead of the depth criteria, the inadequacy of the packaged goods for box handling, storage, and palletization within the logistics facility 190 may be determined by the side on which the non-uniform surface exists and/or the location of the non-uniform surface on that side of the packaged goods (e.g., the region of that side) (and/or other suitable criteria that affect box stability when stacking or automating the transportation/handling of packaged goods). As an example, the vertical side of the palletized load 102 may have stricter inapplicability criteria (e.g., reduced allowance/tolerance for dishing) than the horizontal side of the palletized load 102 because the vertical side acts as a higher load bearing member than the horizontal side when the palletized load is stacked for palletization. Regarding the location of non-uniform surfaces (e.g., depressions, recesses, corrugations, apertures, etc.) on the sides of the packaged goods (e.g., regions of the sides), non-uniform surfaces located at the edges of the packaged goods 102 may be maintained toward a tighter non-suitability criterion (e.g., reduced allowance/tolerance for the depressions) than non-uniform surfaces in the middle/center of the sides. For example, non-uniform surfaces at the edges of the box cargo 102 may provide less stability when stacking the box cargo for palletization, or may create features on the box cargo 102 that cause "catches" or "sharp corners (snag)" that would otherwise interfere with box handling.

Fig. 24A is another exemplary illustration of image data 1400 captured by the flap detection system 170. For illustrative purposes, the image data 140 illustrated in fig. 24 is a front (or back/rear) perspective view of the packaged goods 102, with the box protrusion 2400 present, for example, on top of the packaged goods 102 (note that the protrusion 2400 may be present on any visible side of the packaged goods 102 for detection by the flap detection system 170). Here, the image data 1400 is photographic image data of the packaged goods 102, but may be any other suitable image data that enables image analysis for detecting packaged goods/product characteristics. In a manner similar to that described above, three-dimensional analysis of the packaged goods 102 by the flap detection system 170 determines that, for example, the top side 102T of the packaged goods 102 is a non-conforming surface; although a top side 102T is used as an example, non-uniform surfaces may be present and determined to be on any one or more of the top, lateral and longitudinal sides 102T, 102L, 102R, 102F of the box cargo 102. In one or more aspects, the protrusions may be detected on the bottom surface 102B of the shipment 102, such as based on a determination of the space 2450 formed by the protrusions between the bottom surface 102B of the shipment 102 and the conveyors 110, 120 (e.g., by the flap detection system 170 and/or the profile detection system 180) (see fig. 24B).

Based on the three-dimensional analysis of the packaged goods 102, the flap detection system 170 determines the height 2499 of the protrusion 2400 formed by the non-conforming surface. The height 2499 is measured from, for example, an edge 2424 of the packaged cargo formed by the side of the packaged cargo on which the non-conforming surface is present and the adjacent side of the packaged cargo (where the height 2499 is measured from an edge formed by the top 102T and one or more vertical sides (e.g., lateral sides 102L and/or longitudinal sides 102F, 102R) of the packaged cargo) (see also fig. 11A-11C). In other aspects, the height 2499 may be measured from any other suitable reference point or datum, such as the bottom or the opposite side with respect to the side on which the non-conforming surface is present, in other aspects, instead of or in addition to the determination of the protrusion 2400 by the flap detection system 170, the protrusion 2400 may be determined by the contour detection system 180, and image data from the contour detection system 180 may be used by the flap detection system 170 in a manner similar to that described above for determining the protrusion dimensions (e.g., the three-dimensional contour of the protrusion) and corresponding handling of the packaged cargo to the predetermined form of the container cargo 102, ensuring proper compliance with the bulk storage of the container cargo, the container, the bulk form of the container, and the container, 190, in other aspects.

Here, if the height 2499 of the non-conforming surface is greater than a predetermined threshold (e.g., a bump of about 1 inch (about 25 mm), or in other aspects more or less than about 1 inch (about 25 mm)), then the case cargo 102 is classified as unsuitable (i.e., rejected due to not conforming to the corresponding predetermined case form fit characteristics) for case handling, storage, and palletization within the logistics facility 190, and is removed from automated handling within the logistics facility 190 in the manner described herein. In addition to or instead of the height criteria, the inadequacy of the packaged goods for box handling, storage, and palletization within the logistics facility 190 is determined by the side on which the non-uniform surface is present and/or the location of the non-uniform surface on that side of the packaged goods (e.g., the region of that side) (and/or other suitable criteria that affect box stability when stacking or automating the transportation/handling of packaged goods). As an example, the vertical side of the box cargo 102 may have a different stricter criteria than the horizontal side of the box cargo 102 because the vertical side acts as a higher load bearing member than the horizontal side when the box cargo 102 is stacked for palletization. Regarding the location of the protrusion(s), non-uniform (bulging) surfaces at one corner, diagonal corner, or middle/center of the box cargo 102 may provide less stability when stacking the box cargo for palletization, or may create features on the box cargo that would otherwise interfere with the box handling that induce "catches" or "sharp corners" and may be maintained toward a tighter inappropriateness criterion than the bulging surfaces along substantially the entire edge.

In addition to or instead of the determination of one or more of the above-described box cargo characteristics (e.g., depression, open flap, actual box, maximum protrusion (as determined by one or more of the box inspection system 180 and the flap detection system 170), length of the external box, protrusion/open flap, orientation angle, distance from one side of the conveyor, etc.), the box inspection system 180 and/or the flap detection system 170 (using information from the box inspection system 180) are configured to determine one or more of the following: multiple bin detection (fig. 29), vertical item verification inside the bin load (fig. 26), maximum narrowing at the top and/or bottom of the bin load (fig. 11C, 25 and 27), and tapered (bin load support surfaces (fig. 25 and 26) for achieving a determination of compliance of the respective bin load with predetermined bin form fit characteristics.

Referring to fig. 29, an example plan/top image of a plurality of box cargos 102A, 102B traveling along conveyors 110, 120 is provided. The images illustrated in fig. 29 may be provided by one or more of the bin inspection system 180 and the flap detection system 170. The controller 199 is configured to: each of the plurality of containerized loads 102A, 102B is distinguished using image data obtained from the box inspection system 180 and/or the flap detection system 170, and the characteristics of the containerized loads described herein are determined (in the manner described herein) for each of the containerized loads 102A, 102B.

Referring to fig. 25, an exemplary image (such as an image acquired by the flap detection system 170 and/or the bin inspection system 180) is provided and illustrates a top taper TP3 of the packaged cargo 102. It is noted that the exemplary image shown in fig. 25 is a side view (length axis) of the box cargo 102 having a substantially zero orientation angle. In other aspects, where the orientation angle is substantially 90 degrees, a similar side view (width-wise axis) image is acquired. When the angle of orientation of the palletized load 102 on the conveyors 110, 120 does not provide a facade (e.g., substantially straight side) view, but rather an isometric view of the palletized load 120, then three-dimensional image data from the flap detection system 170 (which in some aspects is used in conjunction with data from the bin inspection system 180) may be employed by the controller 199 to determine the top taper TP3 of the palletized load along one or more of the length and width axes. The top taper TP3 is measured from a plane defined, for example, by the bottom side 102B (i.e., seating surface) of the palletized load 102, which bottom side 102 seats against the surface of the conveyors 110, 120 (or otherwise seats against a support surface in a storage/holding position, or another palletized load of a palletized load stack). When the top taper TP3 exceeds a predetermined threshold (e.g., the predetermined threshold is based on stability of other box cargo stacked on top of the box cargo 102, such as, for example, about 1 inch (about 25 mm) -in other aspects, the predetermined threshold may be more or less than about 1 inch (about 25 mm)), the box cargo is rejected in the manner described herein.

Controller 199 is configured to present top cone TP3 information to the user/operator in any suitable manner, such as through user interface 198. For example, the controller indicates the amount of tapering (along one or more of the length and width axes), the axis along which the tapering is determined (e.g., length or width), and the angle of orientation of the palletized load. When the determination of the top cone TP3 is not available, controller 199 provides (e.g., through user interface 198) an indication of the top cone's unavailability to the user. The top taper may be employed at least when determining a pallet build plan using controller 199.

Still referring to fig. 25, an exemplary image (which is obtained from one or more of the bin inspection system 180 and the flap detection system 170) illustrates top narrowing of the packaged goods 102 in the form of a tray 2520 containing round bottles. The exemplary image is a substantially two-dimensional image of the palletized load 102; in other aspects, however, a three-dimensional image may be provided. Here, the top narrowing indicates a decrease in the value (i.e., surface area) of the top 102T relative to the bottom 102B of the box cargo 102. Here, the leading longitudinal side 102F of the box cargo 102 includes a taper having an angle TP1, as measured from, for example, a plane defined by the non-tapered portion of the longitudinal side 102F. The trailing longitudinal side 102R of the box cargo 102 includes a taper having an angle TP2 as measured from, for example, a plane defined by the non-tapered portion of the longitudinal side 102R. These tapers TP1, TP2 translate into narrowing values DP1, DP2 that inform the reduced surface area of the top 102T of the palletized load relative to the bottom 102B.

The narrowing values DP1, DP2 may affect the capacity of the palletized load such that the reduced surface area (i.e., the support surface) of the top portion 102T caused by the tapers TP1, TP2 cannot stably support other palletized loads 102 stacked thereon. When the packaged goods 102 are substantially symmetrical, such as for the case of packaged goods comprising round bottles as in fig. 25, the greater of the narrowing values DP1, DP2 is assumed for both the length-direction and width-direction axes of the packaged goods; while in other aspects, the taper TP1, TP2 and resulting narrowing values DP1, DP2 may be determined (such as from three-dimensional image data from the flap detection system 170, or a combination of image data from both the flap detection system 170 and the bin inspection system 180) for each side 102F, 102R, 102L1, 102L2 of the palletized load 102. In other aspects, such as where the shipment 102 includes asymmetric content (e.g., such as a salad dressing bottle having one flat side and one side including a bottle neck taper), the narrowing values DP1, DP2 are provided for only one of the length and width axes, but the greater of the narrowing values DP1, DP2 are assumed for both the length and width axes. In the case of a bottle, the maximum narrowing value may be substantially the same as the expected distance EDP between the rim 2510 defined by the tray/package 2520 holding the bottle and the outer perimeter of the bottle cap 2530 (see fig. 25A); while in other aspects the maximum narrowing value may be greater or less than the expected distance EDP.

Referring to fig. 27, an exemplary image (which is obtained from one or more of the box inspection system 180 and the flap detection system 170) illustrates a narrowing of the top of the packaged goods 102 in the form of boxes. The exemplary image is a substantially two-dimensional image of the palletized load 102; in other aspects, however, a three-dimensional image may be provided. In the illustrated example, the narrowing values DP1, DP1 inform the tilted/deformed box; however, in other aspects, the narrowing values DP1, DP2 may be indicative of a decrease in the value (i.e., surface area) of the top 102T of the palletized load 102 relative to the bottom 102B, such as where the top 102T of the palletized load is creased (see fig. 23) or otherwise deformed. Here, the top edge TEF of the box cargo 102 on the leading lateral side 102L1 is offset by a narrowing value DP1, which narrowing value DP1 is relative to the bottom edge BEF of the box cargo 102 on the leading lateral side 102L 1. Here, the top edge TER of the box cargo 102 on the trailing lateral side 102L2 is offset in the same direction as the top edge TEF by a narrowing value DP2, which narrowing value DP2 is relative to the bottom edge BER of the box cargo on the trailing lateral side 102L 2. Narrowing of the top edges TEF, TER in the same direction informs of the inclination of the box cargo 102, which may affect the stability of the box cargo 102, such as when palletized, because the inclination may cause repositioning of the center of gravity of the box cargo from CG1 to CG 2. In one or more aspects, the greater of the narrowing values DPI, DP2 informing of the inclination of the box cargo 102 is assumed for both the width-wise and length-wise axes. In the case of a box-style packaged cargo 102, the maximum narrowing value may be about 1 inch (about 25 mm); while in other aspects the maximum narrowing value may be greater than or less than about 1 inch (about 25 mm).

In the above example, if the narrowing values DP1, DP2 exceed the predetermined maximum narrowing values, then the box cargo 102 is rejected in the manner described herein. In a manner similar to that described above, the maximum narrowing value may be based on the stability of the packaged goods when palletized. In one or more aspects, the determined narrowing values DP1, DP1 of the top 102T and/or bottom 102B of the box cargo 102 are presented to the operator by the controller 199 through the user interface 198 in any suitable manner. The narrowing value (e.g., which tells one or more of the inclined and support surfaces) may be employed at least when utilizing controller 199 to generate a pallet build plan. The narrowing value (e.g., which tells about the tilt) can be used to reject at least the following bin: otherwise the box will be mishandled (not picked up, not stably supported, etc.) by automation within the logistics facility 190.

Referring also to fig. 11C, some of the shipment characteristics described herein may not be mutually exclusive. For example, as can be seen in fig. 11C, the narrowing and bulge of the box cargo 102 may not be mutually exclusive (e.g., the narrowing and bulge may be mutually inclusive). In examples where more than one mutually inclusive shipment characteristic is determined, controller 199 is configured to identify the mutually inclusive characteristic in accordance with the above description. For example, while narrowing the palletized load 102 present in fig. 11C, the top edge TEF generally depicts a narrowed boundary (terminal). The controller 199 is configured to distinguish between a generally flat surface (or a generally constant spacing) that lags behind the narrowed portion of the longitudinal side 102R and a variable spacing that signals the protrusions in the top 102T of the box cargo 102. Here, the controller 199 is configured to determine the bulge from the top edge TE as identified by the change in the spacing of the trailing longitudinal side 102R. In other aspects, the controller 199 is configured to distinguish between the different shipment characteristics described herein in any suitable manner.

Referring to fig. 26, an exemplary image illustrating vertical item verification inside a box cargo (which is obtained from one or more of the box inspection system 180 and the flap detection system 170) is provided. The exemplary image is a substantially two-dimensional image of the palletized load 102; however, in other aspects, a three-dimensional image may be provided. Vertical item verification provides one or more of the following: an indication of the number of different vertical articles observed for the inspection axis (e.g., the length-wise axis and/or the width-wise axis), an indication of the average width 2610 of the tops of one vertical article (such as bottle cap 2530) as observed for the inspection axis, and an indication of the average width 2620 of the gap between the tops of adjacent vertical articles (such as bottle cap 2530) as observed for the inspection axis. The above information obtained from vertical item verification may be employed by controller 199 at least in generating a tray build plan. In the illustrated example, the box cargo 102 is similar to the case of round bottles illustrated in fig. 25.

Here, the controller 199 is configured to determine the number of vertical articles within the packaged good 102 from the image data obtained from one or more of the box inspection system 180 and the flap detection system 170 (in the example shown, there are four vertical articles configured along the length-wise axis; but in other aspects, the three-dimensional image data from the flap detection system 180 may be employed with or in place of the two-dimensional image data from the box inspection system 180 to determine the number of vertical articles along one or more of the length-wise and width-wise axes). It is noted that the number of vertical items may be presented to the operator by controller 199 through user interface 198 in any suitable manner (note that a plurality of vertical items for the packaged goods in box form are indicated as one vertical item).

The controller 199 is configured to determine from image data obtained from one or more of the bin inspection system 180 and the flap detection system 170 an average width 2610 of the top of one vertical item (such as the bottle cap 2530) as viewed for the inspection axis (in the example shown, the inspection axis is a lengthwise axis; but in other aspects, three-dimensional image data from the flap detection system 180 may be employed with or in place of two-dimensional image data from the bin inspection system 180 to determine an average width 2610 of the top of one vertical item along one or more of the lengthwise and widthwise axes). It is noted that the average width 2610 of the top of one of the vertical items may be presented to the operator by the controller 199 through the user interface 198 in any suitable manner (note that the average width 2610 of the top of one of the vertical items for the box of packed goods in the form of a box is substantially equal to the entire top surface of the box).

The controller 199 is configured to determine from image data obtained from one or more of the box inspection system 180 and the flap detection system 170 an average width 2620 of the gap between tops of adjacent vertical articles (such as the bottle caps 2530) as viewed for the inspection axis (in the example shown, the inspection axis is a lengthwise axis; but in other aspects, three-dimensional image data from the flap detection system 180 may be employed with or in place of two-dimensional image data from the box inspection system 180 to determine an average width 2620 of the gap between tops of adjacent vertical articles). Note that the average width 2620 of the gap between the tops of adjacent vertical items may be presented to the operator by controller 199 through user interface 198 in any suitable manner (note that the average width 2620 of the gap between the tops of adjacent vertical items for box-packed cargo is substantially equal to zero).

As described above, the flap detection system 170 (using data from the bin inspection system 180) and the profile detection system 180 determine whether the packaged goods 102 that have passed through the profile detection system 180 are suitable for storage, disposal, and palletization in the logistics facility 190. For example, as described above, at least one conveyor 110, 120 advances the packaged goods 102 into the logistics facility 190. The bin inspection station 180 is configured to communicate with at least one conveyor 110, 120 such that the packaged goods 102 advance through the bin inspection system 180. The bin inspection system 180 has at least one bin inspection camera (e.g., sensor/imaging devices 181, 184) arranged to capture images of shadows of each bin load 102 advanced through the bin inspection system 180. At least one other camera 171-173 (e.g., flap detection system 170) is connected to the bin inspection station 180, the at least one other camera 171-173 being separate and distinct from the at least one sensor/imaging device 181, 184. The at least one further camera 171-173 is arranged to capture other bin image data of each bin load 102 advanced through the bin inspection system 180 in addition to the bin image data captured by the at least one sensor/imaging device 181, 184.

Here, the processor 199P of the controller 199 is operatively coupled to at least one conveyor 110, 120. The processor 199P is also communicatively coupled to the at least one sensor/imaging device 181, 184 to receive the bin image data from the at least one sensor/imaging device 181, 184. The processor 199P is further communicatively coupled to at least one other camera 171-173 to receive other box image data for each box cargo 102 from the at least one other camera 171-173. Here, the processor 199P (and thus the controller 199) is configured to determine predetermined characteristics of each shipment 102 (such as those described above) that determine the bin form from the image of the shadow of each shipment 102 imaged by the at least one sensor/imaging device 181, 184, thereby confirming that the respective shipment has a bin shape. The predetermined characteristics of each of the shipment 102 in the form of a decision box include one or more of the following: the box length, box width, box height, the included angle between the box sides, box dimensions (see fig. 13A-20, 25A, 27, 28A and 28B), and any other suitable physical property of the box-packed cargo that determines the box form, such as those described herein.

The processor 199P/controller 199 is configured such that upon confirming that the respective box cargo 102 has a box shape, compliance of the respective box cargo 102 with predetermined box form fit characteristics (such as those described above) is determined from other image data (e.g., from the flap detection system 170). As described herein, the predetermined bin form fit characteristics inform of the fit acceptance of the respective packaged goods 102 within a predetermined fit space or location of the logistics facility 190 (e.g., storage space or other holding location of the storage array 190SA, payload bins of the automated transport vehicle 190ATV, pallet load build location in a pallet build formed in the logistics facility 190, etc.).

For example, referring to fig. 28A and 28B, any given box cargo stored/handled by the logistics facility has a corresponding expected size in at least box length, box width, and box height (note that the amount of narrowing and/or tapering, the number of individual items held, the gaps between individual items, and the width of the top of individual items also have the expected size). These desired dimensions define predetermined bin shape and form adaptations for the corresponding bin load 102 to be inserted into the logistics facility 190, noting that each identical stock unit (SKU) admitted to/inserted into the logistics facility 190 has a desired bin size defining the form adaptations of that SKU. The expected dimensions are measured from a predetermined reference baseline of the packaged goods 102 such that the uniformity of packaged goods exists between packaged goods of the same type (i.e., the same SKU). For example, as illustrated in fig. 28A, the tank length dimension is measured from the length-determining reference plane, and the tank width dimension is measured from the width-determining reference plane. The length-determining reference plane and the width-determining reference plane lie in, for example, a vertical plane defined by one of the lateral sides (e.g., side 102L 1) and a vertical plane defined by one of the longitudinal sides (e.g., side 102R). As can be seen in fig. 28B, the bin height dimension is measured from a height defined by the bottom side 102B (or seating surface) of the packaged cargo 102 to determine a reference plane. These datum planes enable bin load position determination such as by, but not limited to, controller 199, pallet stacker 190P, and automated transport vehicle 190ATV for positioning bin load 102 on, but not limited to, storage racks in storage array 190SA, on pallets in pallet loads, on automated transport vehicle 190ATV (for robotic grasping by pallet stacker 190P), and on a face builder (face builder) such as any suitable bin handling equipment of a logistics facility configured to form a face (face), including, but not limited to, automated transport vehicle 190ATV and a face builder such as those described in U.S. patent No. 9475649 (entitled "Pickface Builder for Storage and Retrieval Systems") issued 10 month 25 in 2016, previously incorporated herein by reference in its entirety for the formation of faces, wherein the face includes more than one bin load transported/handled as a single unit in logistics facility 190, and so forth.

The desired bin length, desired bin width, and desired bin height include tolerances that allow the actual size of the packaged goods to be a predetermined amount above the desired value and a predetermined amount below the desired value. The tolerance may be based on the size of the storage space in the storage array 190SA, the size of the payload bay of the automated transport vehicle 190ATV, the stability of the palletized load in the pallet bin construction, the storage space height limit, or any other suitable structural limit imposed on the palletized load by the structure and operation of the logistics facility 190. These expected dimensions of a given container cargo type (e.g., SKU) including its tolerances define predetermined box-form fit characteristics of the container cargo 102. The determined bin load characteristics determined by the bin inspection system 180 and/or the flap detection system 170 inform the actual bin form fit characteristics of the given bin load inspected by the inspection system 100, and the controller 199 determines compliance of the actual bin form fit characteristics of the given bin load with predetermined bin form fit characteristics defined by the intended dimensions.

As described herein, when one or more of the determined dimensions of the packaged good 102 exceeds the expected dimensions (including any tolerances) of the packaged good 102, the packaged good is rejected and not permitted for the storage, handling, and palletizing process of the logistics facility 190. The tolerance applied to the expected size (e.g., which establishes a pass (go) or no pass (no-go) type criterion for the admission of the type of containerized good into the logistics facility 190) is determined such that, in one aspect, assembly of the containerized good 102 to a storage space or other holding location of the storage array 190SA, a payload bin of the automated transport vehicle 190ATV, a tray load build location in a tray build formed in the logistics facility 190, and any other suitable location of the logistics facility 190 is generally ensured for containerized good 102 that falls within about two standard deviations of the gaussian distribution of containerized good 102 handled by the logistics facility 190 for a given number of containerized good inspected by the containerized good inspection system 100; while in other aspects, assembly of the packaged goods 102 is generally ensured for packaged goods 102 that fall within about three standard deviations of the gaussian distribution of packaged goods handled/inspected by the logistics facility 190. Here, generally ensuring that the form fit or fitting of the box cargo that falls within about two standard deviations (or in some aspects, three standard deviations) for any given number of box cargos 102 inspected by the box cargo inspection system 100 provides for each box cargo 102 within the logistics facility: is substantially always recordable in the face-picking builder, positionable on a pallet (or other suitable stored palletized load holding location), is recordable for pick and place of palletized loads by the arm tool end of the palletizing robot of the pallet stacker 190P, and/or is substantially always stackable in the pallet load formed by the pallet stacker 190P.

In operation, the flap detection system provides a binary result regarding the presence of open flaps (i.e., open flaps: yes/no), while the length, width, and height of the packaged goods are measured by the profile detection system 180. As an example, the result of the open flap detection is true when the dimensions of the box cargo 102 are recorded in the controller 199 as 8 units in width, 10 units in length, and 6 units in height and the box cargo inspection system 100 returns a result of the box cargo 102 having 8 units in width, 13 units in length, and 6 units in height based on the inspection of the box cargo 102. It is noted that the acceptable tolerance of the size of the palletized load (e.g., with and without the presence of the open flaps) may depend on the palletizing capability of the automated palletizing load handling apparatus downstream (i.e., after the palletizing load inspection system 100). For example, table 1 below illustrates the pass/fail rate of the box cargo through the box cargo inspection system 100, where the box cargo dimensional tolerance is set to 1 unit (e.g., about 1 inch or about 25mm—the linear dimension in table 1 is in millimeters and the angular dimension is in degrees), and a "1" in the pass/fail column indicates rejected box cargo 102 and a "0" in the pass/fail column indicates accepted box cargo 102.

Table 1:

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as can be seen in table 1 above, the palletized load 102 is rejected when, for example, a 1 inch or 25.4mm tolerance is employed. However, as noted above, the acceptable tolerance of the containerized cargo size (e.g., with and without the presence of the open flaps) may depend on the containerized cargo handling capability of the automated containerized cargo handling device downstream (i.e., after the containerized cargo inspection system 100). Thus, when the downstream automated bin handling equipment is able to handle bins having a tolerance of about 2 inches or 50mm, the acceptance rate of the same bin load increases, as shown in table 2 below:

table 2:

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it is noted with respect to table 2 that for the same packaged goods, the indication of the open flap has changed from the indication in table 1 because of the following conditions: for an open flap to be detected, a minimum number of parameters must be met. In the examples of tables 1 and 2, all parameters (note that the flap depth parameter is accounted for in the flap length and bin length parameters) should be met before the open flap is detected. In the case of table 2, the increased tolerance reduces the number of detected open flaps and increases the number of accepted palletized loads.

The process may also determine that the open flaps extend in one or more of the length, width, height of the packaged goods 102 by comparing the expected packaged goods size to the actual (i.e., measured) packaged goods size and the presence of the open flaps. This information, as well as any other suitable information, may be presented to an operator via the user interface 198, as described herein. The flap detection system 170 supports open flap detection of the packaged goods 102 that are not located on any of the five visible sides on the conveyors 110, 120. In one or more aspects, the flap detection system 170 uses the box image data to estimate a core size (e.g., length, width, and height without any box-exterior protrusions or open flaps) of the packaged goods, even if open flaps and/or box-exterior protrusions are present. Here, the flap detection system 170 includes any suitable number of sensors 171-173 (such as more than two, or employing mirrors to view the packaged goods from more than two angles) such that imaging of the packaged goods side is not obscured or otherwise blocked by the open flaps. The estimation of the core size of the palletized load 102 by the flap detection system 170 may verify the acceptance or rejection of any given palletized load by the contour detection system 180. For example, when the containerized good is rejected by the contour detection system 180 because one or more of the length, width, and/or height exceeds a corresponding predetermined (e.g., intended) length, width, and/or height due to the open flap (i.e., the core size of the containerized good is within the tolerance but the presence of the open flap causes an out-of-tolerance condition to be detected by the contour detection system 180), the flap detection system 170 verifies that the out-of-tolerance condition is due to the open flap and verifies that the open flap can be handled by downstream (i.e., after the containerized good inspection system 100) automated equipment. When the box cargo with the open flaps cannot be handled by downstream automated equipment, the box cargo may be rejected.

Referring to fig. 1, 1A-1C and 22, a method for inspecting a packaged cargo 102 in accordance with one or more aspects of the disclosed embodiments will be described. According to the method, the packaged goods 102 are advanced through the packaged goods inspection system 100 using at least one conveyor 110, 120 (fig. 22, block 2200). The at least one sensor 171-173 captures bin image data 1400 (fig. 14A-14D and 22, block 2210) of each of the bins 102 advanced through the bin load inspection system 100 using the at least one conveyor 110, 120. Processor 199P is provided (fig. 22, block 2220), wherein in one or more aspects processor 199P characterizes box exterior protrusion 220 (fig. 2A and 2B) of box cargo 102 from box image data as box flaps in an open condition (fig. 22, block 2230), wherein processor 199P is configured to parse box image data 1400 and determine that box exterior protrusion 220 is a uniform flat surface 1410 (fig. 14A-14D), and is programmed with parameter array 199A of physical characteristic parameters describing box flap uniformity attributes that determine a uniform flat surface 1410 defining an open box flap condition. In one or more aspects, processor 199P parses box image data 1400 and determines that box exterior protrusion 220 is a uniform flat surface 1410 (fig. 22, block 2240). The processor 199P generates a physical property array 199C (fig. 22, block 2250) from the bin image data 1400 for each determined consistent flat surface 1410, and applies the parameter array 199A to the physical property array 199C to resolve the consistent flat surface 1410 into an open bin flap.

Referring now to fig. 1, 1A-1C, 2B, 23A and 29, a method in an inspection apparatus for inspecting a packaged cargo will be described. In the method, at least one conveyor 110, 120 advances a packaged cargo 102 through a testing apparatus 100 (fig. 30, block 3000). At least one camera 171-173 captures bin image data for each bin load 102 advanced through the inspection device 100 using at least one conveyor 110, 120 (fig. 30, block 3010). A processor 199P is provided (fig. 30, block 3020) and receives bin image data 1400 from at least one camera 171-173. As described herein, the processor 199P is operably coupled to the at least one conveyor 110, 120 and communicatively coupled to the at least one camera 171-173, and the processor 199P is configured to characterize at least one of the bin side recess and the bin exterior protrusion of the bin cargo as a bin flap in an open condition (fig. 30, blocks 3030 and 3045) from the bin image data 1400 generated from the common image of the bin cargo 102 captured by the at least one camera 171-173 and parsed by the processor 199P (fig. 30, block 3040).

The processor 199P parses the bin image data (see fig. 30, block 3040) and determines that the bin exterior protrusion 220 is a uniform planar surface, the processor is programmed with a parameter array 199A of physical characteristic parameters that describe bin flap uniformity attributes that determine a uniform planar surface defining an open bin flap condition. The processor generates a physical characteristics array 199C from the bin image data 1400 for each determined consistent flat surface (fig. 30, block 3050), and applies a parameter array 199A to the physical characteristics array 199C to resolve the consistent flat surface into an open bin flap.

In the method, at least one camera 171-173 is arranged to capture box image data 1400 of each box cargo advanced through the inspection apparatus 100 using at least one conveyor 110, 120 such that the box image data 1400 embodies at least one of a box side recess 2300 and a box exterior protrusion 220, wherein at least one of the box side recess 2300 and the box exterior protrusion 220 is evident on at least one exposed box side 102T, 102L, 102F, 120R, and the at least one exposed box side 102T, 102L, 102F, 120R is disposed in each exposed box side orientation of the box cargo. In this method, another imaging system (e.g., contour detection system 180) is provided. The contour detection system 180 is separate and distinct from the at least one camera 171-173, and the contour detection system 180 images the packaged goods 102 separate and distinct from the at least one camera 171-172 imaging the packaged goods 102 for inspection of the packaged goods 102 other than detection of at least one of the box-side depressions and the open box flaps, as described herein.

In accordance with one or more aspects of the disclosed embodiments, an inspection apparatus for inspecting a packaged cargo is provided. The inspection apparatus includes: at least one conveyor configured to advance a packaged cargo through the inspection apparatus; at least one camera arranged to capture bin image data of each bin load advanced through the inspection device using the at least one conveyor; a processor operatively coupled to the at least one conveyor and communicatively coupled to the at least one camera to receive the bin image data from the at least one camera, wherein the processor is configured to characterize a bin exterior protrusion of a bin load from the bin image data as a bin flap in an open condition, wherein the processor is configured to parse the bin image data and determine that the bin exterior protrusion is a uniform flat surface, and is programmed with a parameter array of physical characteristic parameters describing a bin flap uniformity attribute that determines the uniform flat surface defining an open bin flap condition, and wherein the processor is configured to generate a physical characteristic array from the bin image data for each determined uniform flat surface and apply the parameter array to the physical characteristic array to parse the uniform flat surface into an open bin flap.

According to one or more aspects of the disclosed embodiments, the at least one camera is arranged to image each exposed bin side of each bin load advanced through the inspection device with the at least one conveyor to image the bin exterior protrusion apparent on each imaged exposed bin side.

In accordance with one or more aspects of the disclosed embodiments, the imaged exposed bin side is disposed such that the open bin flap, resolved from the bin exterior protrusion apparent on the imaged exposed bin side, extends from the exposed bin side adjacent to a conveyor seating surface on which the bin load sits.

According to one or more aspects of the disclosed embodiments, the at least one camera is arranged to capture the bin image data of each exposed bin side of each bin load advanced through the inspection device with the at least one conveyor such that the captured bin image data of each bin load embodies each exposed bin side outside the respective bin.

According to one or more aspects of the disclosed embodiments, the at least one camera is arranged to capture box image data of each box cargo advanced through the inspection device with the at least one conveyor such that the box image data embodies the box exterior protrusion, wherein the box exterior protrusion is evident on at least one exposed box side, and the at least one exposed box side is disposed in each exposed box side orientation of the box cargo.

According to one or more aspects of the disclosed embodiments, the at least one exposed bin side imaged by the at least one camera is disposed such that the open bin flap resolved from the bin exterior protrusion apparent on the imaged at least one exposed bin side extends from the at least one exposed bin side adjacent a conveyor seating surface on which bin cargo sits.

According to one or more aspects of the disclosed embodiments, the inspection apparatus further comprises another imaging system separate and distinct from the at least one camera, wherein the other imaging system images different characteristics of the palletized load advanced through the inspection apparatus with the at least one conveyor, the different characteristics being distinct from the physical characteristics in the array of physical characteristics.

In accordance with one or more aspects of the disclosed embodiments, the at least one camera captures bin image data substantially simultaneously with the other imaging system imaging the different characteristic of the bin load.

According to one or more aspects of the disclosed embodiments, the inspection apparatus further comprises another imaging system separate and distinct from the at least one camera, and the other imaging system images the palletized load, the imaging separate and distinct from imaging the at least one camera of palletized load for inspection of palletized load other than detection of the open bin flap.

In accordance with one or more aspects of the disclosed embodiments, the other imaging system images the packaged goods for processor verification of the identity of each packaged good and the compliance of each packaged good with the verified package size parameters.

In accordance with one or more aspects of the disclosed embodiments, the processor is configured such that a box cargo inspection based on a box cargo image from the other imaging system is parsed, the parsing being separate and distinct from parsing the open box flaps from the box image data of the at least one camera.

In accordance with one or more aspects of the disclosed embodiments, the processor is configured to determine the presence of the bin exterior protrusion from imaging of the other imaging system separate and distinct from the bin image data captured with the at least one camera, and to resolve the bin exterior protrusion from the bin image data of the at least one camera separate and distinct from the image of the other imaging system into an open bin flap.

In accordance with one or more aspects of the disclosed embodiments, the processor is configured to determine the presence of the bin exterior protrusion from the bin image data captured by the at least one camera independent of an image of the bin cargo captured by the other imaging system.

In accordance with one or more aspects of the disclosed embodiments, an inspection apparatus for inspecting a packaged cargo is provided. The inspection apparatus includes: at least one conveyor configured to advance a packaged cargo through the inspection apparatus; at least one camera arranged to capture bin image data of each bin load advanced through the inspection device using the at least one conveyor; a processor operably coupled to the at least one conveyor and communicatively coupled to the at least one camera to receive the bin image data from the at least one camera, wherein the processor is configured to characterize a bin exterior protrusion of a bin load as an open bin flap from the bin image data, wherein the processor is configured to: the method includes parsing the bin image data and determining that the bin exterior protrusions are uniform flat surfaces, and generating a physical property array of physical properties of the uniform flat surfaces from the bin image data for each determined uniform flat surface such that the physical property array describes the uniform flat surface as a bin flap, and determining that the bin flap is in an open flap condition based on a parameter array of physical property parameters.

In accordance with one or more aspects of the disclosed embodiments, the parameter array of physical characteristic parameters describes a box flap uniformity attribute that determines the uniform planar surface defining the open box flap condition.

In accordance with one or more aspects of the disclosed embodiments, a method for inspecting containerized cargo is provided. The method comprises the following steps: utilizing at least one conveyor to advance the palletized load through the inspection apparatus; utilizing at least one camera to capture bin image data of each bin load advanced through the inspection device utilizing the at least one conveyor; providing a processor operably coupled to the at least one conveyor and communicatively coupled to the at least one camera to receive the bin image data from the at least one camera, and wherein the processor: characterizing a box exterior protrusion of a box cargo as a box flap in an open condition from the box image data, wherein the processor is configured to parse the box image data and determine that the box exterior protrusion is a uniform flat surface and is programmed with a parameter array of physical characteristic parameters describing box flap uniformity attributes that determine the uniform flat surface defining an open box flap condition, and wherein the processor generates a physical characteristic array from the box image data for each determined uniform flat surface and applies the parameter array to the physical characteristic array to parse the uniform flat surface into an open box flap.

According to one or more aspects of the disclosed embodiments, the method further comprises: providing another imaging system separate and distinct from the at least one camera; and imaging, with the another imaging system, different characteristics of the palletized load advanced through the inspection device with the at least one conveyor, the different characteristics being different from the physical characteristics in the array of physical characteristics.

According to one or more aspects of the disclosed embodiments, the method further comprises: providing another imaging system separate and distinct from the at least one camera; and imaging the palletized load with the another imaging system, the imaging being separate and distinct from the imaging of the at least one camera of palletized load for inspection of palletized load other than detection of the open bin flap.

In accordance with one or more aspects of the disclosed embodiments, a method for inspecting containerized cargo is provided. The method comprises the following steps: utilizing at least one conveyor to advance the palletized load through the inspection apparatus; utilizing at least one camera to capture bin image data of each bin load advanced through the inspection device utilizing the at least one conveyor; providing a processor operably coupled to the at least one conveyor and communicatively coupled to the at least one camera to receive the bin image data from the at least one camera, and wherein the processor: characterizing box exterior protrusions of box-packed goods as open box flaps from the box image data; parsing the bin image data and determining that the bin exterior protrusion is a uniform flat surface; and generating a physical property array of physical properties of the conforming planar surface from the bin image data for each determined conforming planar surface such that the physical property array describes the conforming planar surface as a bin flap and determines that the bin flap is in an open flap condition based on a parameter array of physical property parameters.

In accordance with one or more aspects of the disclosed embodiments, an inspection apparatus for inspecting a packaged cargo is provided. The inspection apparatus includes: at least one conveyor configured to advance a packaged cargo through the inspection apparatus; at least one camera arranged to capture bin image data of each bin load advanced through the inspection device using the at least one conveyor; a processor operably coupled to the at least one conveyor and communicatively coupled to the at least one camera to receive the bin image data from the at least one camera; and wherein the processor is configured to characterize at least one of a bin-side recess and a bin-exterior protrusion of the packaged cargo as a bin flap in an open condition from the bin image data generated from a common image of the packaged cargo captured by the at least one camera.

In accordance with one or more aspects of the disclosed embodiments, the processor is configured to parse the bin image data and determine that the bin exterior protrusion is a uniform planar surface, and is programmed with a parameter array of physical characteristic parameters describing bin flap uniformity attributes that determine the uniform planar surface defining an open bin flap condition.

In accordance with one or more aspects of the disclosed embodiments, the processor is configured to generate a physical characteristics array from the box image data for each determined consistent flat surface and apply the parameter array to the physical characteristics array to resolve the consistent flat surface into an open box flap.

According to one or more aspects of the disclosed embodiments, the at least one camera is arranged to image each exposed bin side of each bin load advanced through the apparatus with the at least one conveyor to image at least one of the bin side recess and the bin exterior protrusion apparent on each imaged bin side from the common image of each imaged bin side.

According to one or more aspects of the disclosed embodiments, the at least one camera is arranged to capture case image data of each case cargo advanced through the inspection device with the at least one conveyor such that the case image data embodies at least one of the case side recess and the case exterior protrusion, wherein the at least one of the case side recess and the case exterior protrusion is evident on at least one exposed case side, and the at least one exposed case side is disposed in each exposed case side orientation of the case cargo.

According to one or more aspects of the disclosed embodiments, the at least one exposed bin side imaged by the at least one camera is disposed such that at least one of the bin side recess and the bin flap in an open condition, as resolved from at least one of the bin side recess and the bin exterior protrusion evident on the imaged at least one exposed bin side, extends from the at least one exposed bin side adjacent a conveyor seating surface on which bin cargo sits.

According to one or more aspects of the disclosed embodiments, the inspection apparatus further comprises another imaging system separate and distinct from the at least one camera, and the other imaging system images the packaged goods, the imaging separate and distinct from imaging the at least one camera of the packaged goods for inspection of packaged goods other than detection of at least one of the box-side recess and the open box flap.

In accordance with one or more aspects of the disclosed embodiments, the processor is configured such that a box cargo inspection based on a box cargo image from the other imaging system is parsed, the parsing being separate and distinct from parsing at least one of the box side recess and the open box flap from the box image data of the at least one camera.

In accordance with one or more aspects of the disclosed embodiments, the processor is configured to determine the presence of at least one of the bin-side recess and the bin-exterior protrusion of the bin load from imaging of the other imaging system separate and distinct from the bin image data captured with the at least one camera, and to parse the at least one of the bin-side recess and the bin-exterior protrusion into respective bin recesses and open bin flaps from the bin image data of the at least one camera separate and distinct from the image of the other imaging system.

According to one or more aspects of the disclosed embodiments, the processor is configured to determine the presence of at least one of the bin-side recess and the bin-exterior protrusion on a bin-cargo side from the bin image data captured by the at least one camera independent of an image of the bin-cargo captured by the other imaging system.

In accordance with one or more aspects of the disclosed embodiments, an inspection apparatus for inspecting a packaged cargo is provided. The inspection apparatus includes: at least one conveyor configured to advance a packaged cargo through the inspection apparatus; at least one camera arranged to capture bin image data of each bin load advanced through the inspection device using the at least one conveyor; a processor operably coupled to the at least one conveyor and communicatively coupled to the at least one camera to receive the bin image data from the at least one camera, wherein: the processor is configured to characterize at least one bin top or at least one bin side having a dishing condition from the bin image data of bin cargo captured by the at least one camera, wherein the processor is programmed to resolve from the image data an inward shift of a predetermined planar uniformity characteristic of the at least one bin top or the at least one bin side with the bin top or bin side; and the processor is configured to determine, from the image data, a physical characteristic describing a dishing condition of the at least one bin top or the at least one bin side for each resolved inwardly varying presence.

In accordance with one or more aspects of the disclosed embodiments, the processor is configured to parse the bin image data and determine that the at least one bin top or the at least one bin side has an inward variation, and is programmed with a parameter array of physical characteristic parameters describing an inward variation attribute that determines the inward variation defining a dishing condition.

In accordance with one or more aspects of the disclosed embodiments, the processor is configured to generate a physical characteristics array from the bin image data for each determined inward variation, and apply the parameter array to the physical characteristics array to resolve the inward variation to a dishing condition.

According to one or more aspects of the disclosed embodiments, the at least one camera is arranged to image each exposed bin side of each bin load advanced through the inspection device with the at least one conveyor to image a dishing condition evident on each imaged bin side from the common image of each imaged bin side.

According to one or more aspects of the disclosed embodiments, the at least one camera is arranged to capture box image data of each box cargo advanced through the inspection device with the at least one conveyor such that the box image data embodies a recessed condition, wherein the recessed condition is evident on at least one exposed box side, and the at least one exposed box side is disposed in each exposed box side orientation of the box cargo.

According to one or more aspects of the disclosed embodiments, the at least one exposed bin side imaged by the at least one camera is disposed such that a recess condition resolved from a recess condition apparent on the imaged at least one exposed bin side extends from the at least one exposed bin side adjacent a conveyor seating surface on which the box cargo sits.

According to one or more aspects of the disclosed embodiments, the inspection apparatus further comprises another imaging system separate and distinct from the at least one camera, and the other imaging system images the packaged goods, the imaging separate and distinct from the at least one camera imaging the packaged goods for inspection of the packaged goods in addition to detection of the dent condition.

In accordance with one or more aspects of the disclosed embodiments, the processor is configured such that a box cargo inspection based on a box cargo image from the other imaging system is parsed, the parsing being separate and distinct from parsing the recess condition from the box image data of the at least one camera.

In accordance with one or more aspects of the disclosed embodiments, the processor is configured to determine the presence of a dent condition box cargo from imaging of the another imaging system separate and distinct from the box image data captured with the at least one camera, and resolve the dent condition to a box dent from the box image data of the at least one camera separate and distinct from the image of the another imaging system.

In accordance with one or more aspects of the disclosed embodiments, the processor is configured to determine the presence of a recessed condition bin cargo from the bin image data captured by the at least one camera independent of an image of the bin cargo captured by the other imaging system.

In accordance with one or more aspects of the disclosed embodiments, an inbound conveyor system for guiding containerized goods in a logistics facility is provided. The system comprises: at least one conveyor configured to push box-packed cargo into the logistics facility; a bin inspection station arranged to communicate with the at least one conveyor such that bin contents advance through the bin inspection station, the bin inspection station having at least one bin inspection camera configured to capture an image of a shadow of each bin contents advanced through the bin inspection station; at least one further camera connected to the bin inspection station, separate and distinct from the at least one bin inspection camera, and arranged to capture other bin image data of each bin load advanced through the bin inspection station in addition to the bin image data captured by the at least one bin inspection camera; and a processor operatively coupled to the at least one conveyor, communicatively coupled to the at least one bin inspection camera, to receive the bin image data from the at least one bin inspection camera, and communicatively coupled to the at least another camera, to receive the other bin image data for each bin load from the at least another camera, wherein the processor is configured to determine predetermined characteristics of each bin load in a decision bin form from the image of the shadow of each bin load imaged by the at least one bin inspection camera, thereby confirming that the respective bin load has a bin shape, and wherein the processor is configured to determine compliance of the respective bin load with the predetermined bin form fit characteristics from the other image data after confirming that the respective bin load has the bin shape.

In accordance with one or more aspects of the disclosed embodiments, the predetermined bin form fit characteristics inform of the assembly acceptance of the respective bin load within a predetermined assembly space or location of a storage array of the logistics facility.

According to one or more aspects of the disclosed embodiments, the predetermined assembly space or location is a pallet load build location formed in a pallet build in the logistics facility.

According to one or more aspects of the disclosed embodiments, the predetermined bin form fitting characteristic is an inward protrusion or depression of at least one side of the bin shape of the respective bin load relative to a flat bin side.

In accordance with one or more aspects of the disclosed embodiments, the predetermined characteristics that determine each of the palletized load in the box form include one or more of box length, box width, box height, included angle between box sides, box size.

In accordance with one or more aspects of the disclosed embodiments, the processor comprises: an image acquisition assembly configured to acquire more than one digitized image from the bin inspection station for each bin load advanced through the bin inspection station; and an image combiner configured to selectively combine a plurality of acquired digitized images other than the more than one digitized image into a combined image based on a continuous input beam spatial intensity reduction below a first threshold for a duration of the more than one of the acquired digitized images.

In accordance with one or more aspects of the disclosed embodiments, the processor is configured to identify the presence of the translucent shrink wrap disposed on the product in the box cargo based on the continuous input beam spatial intensity reduction being below a second threshold to confirm the presence of the box cargo.

According to one or more aspects of the disclosed embodiments, the image combiner is configured to selectively combine the acquired digitized images into a potential product combination image, wherein a plurality of pixels digitized in the image having a reduced intensity below a first predetermined threshold define an image width greater than a second threshold.

According to one or more aspects of the disclosed embodiments, the image combiner is configured to selectively combine the acquired digitized images to form the combined image, wherein the plurality of pixels digitized across sequential images having reduced intensities below a first predetermined threshold and a second threshold represent a predetermined combined image length.

In accordance with one or more aspects of the disclosed embodiments, the at least one conveyor is configured to advance the packaged goods at an advancement rate, and the image acquisition assembly is configured to acquire the digitized images at an acquisition rate proportional to the advancement rate of the packaged goods.

In accordance with one or more aspects of the disclosed embodiments, the image acquisition rate is synchronized through the use of an encoder or through stepper motor drive circuitry.

In accordance with one or more aspects of the disclosed embodiments, the image acquisition component includes an image cache.

In accordance with one or more aspects of the disclosed embodiments, the at least one bin inspection camera is configured to determine ambient light intensity from a sample buffer of cached images.

According to one or more aspects of the disclosed embodiments, the processor is configured to determine a size from the combined image of: a first shape best fit in the combined image, a second shape bounding the combined image, and a difference between the first shape and the second shape.

According to one or more aspects of the disclosed embodiments, the processor is configured to determine an orientation angle of the palletized load with respect to the at least one conveyor from the combined image.

According to one or more aspects of the disclosed embodiments, the processor is configured to determine a distance of the palletized load from a side of the at least one conveyor from the combined image.

In accordance with one or more aspects of the disclosed embodiments, the bin inspection station is configured to identify the presence of debris on an input window of the at least one bin inspection camera based on common pixels of the same intensity across the plurality of digitized images.

In accordance with one or more aspects of the disclosed embodiments, a method in an inspection apparatus for inspecting a packaged cargo is provided. The method comprises the following steps: utilizing at least one conveyor to advance the palletized load through the inspection apparatus; utilizing at least one camera to capture bin image data of each bin load advanced through the inspection device utilizing the at least one conveyor; and providing a processor and utilizing the processor to receive the bin image data from the at least one camera, wherein the processor is operably coupled to the at least one conveyor and communicatively coupled to the at least one camera, and the processor is configured to characterize at least one of a bin side recess and a bin exterior protrusion of a bin cargo as being in an open condition from the bin image data generated from a common image of the bin cargo captured by the at least one camera.

In accordance with one or more aspects of the disclosed embodiments, the processor parses the bin image data and determines that the bin exterior protrusion is a uniform planar surface, the processor being programmed with a parameter array of physical characteristic parameters describing bin flap uniformity attributes that determine the uniform planar surface defining an open bin flap condition.

In accordance with one or more aspects of the disclosed embodiments, the processor generates a physical property array from the bin image data for each determined consistent planar surface and applies the parameter array to the physical property array to resolve the consistent planar surface into an open bin flap.

In accordance with one or more aspects of the disclosed embodiments, the method further includes utilizing another imaging system separate and distinct from the at least one camera to image the palletized load, the imaging separate and distinct from the at least one camera imaging the palletized load for inspection of palletized loads other than detection of at least one of the box side recess and the open box flap.

In accordance with one or more aspects of the disclosed embodiments, the processor determines the presence of at least one of the bin-side recess and the bin-exterior protrusion of bin cargo from imaging of the other imaging system separate and distinct from the bin-image data captured with the at least one camera, and parses the at least one of the bin-side recess and the bin-exterior protrusion into respective bin recesses and open bin flaps from the bin-image data of the at least one camera separate and distinct from the image of the other imaging system.

In accordance with one or more aspects of the disclosed embodiments, the processor determines the presence of at least one of the bin-side recess and the bin-exterior protrusion on the bin-cargo side from the bin image data captured by the at least one camera independent of an image of the bin-cargo captured by the other imaging system. Although some reference is made herein to a "vision system," aspects of the disclosed embodiments are not limited to any single camera system operating in the millimeter wave, infrared, vision, microwave, X-ray, gamma ray, etc. spectrum, nor to any combination of camera systems. Although a compound camera may be employed, separate spectrum-specific cameras may also be employed, either plural or in combination. Any reference to a shipment comprising food material (or other content) is incidental and is not intended to limit the scope of any appended claims.

It is to be understood that the foregoing description is only illustrative of aspects of the disclosed embodiments. Various alternatives and modifications can be devised by those skilled in the art without departing from aspects of the disclosed embodiments. Accordingly, aspects of the disclosed embodiments are intended to embrace all such alternatives, modifications and variances that fall within the scope of any appended claims. Furthermore, the mere fact that different features are recited in mutually different dependent or independent claims does not indicate that a combination of these features cannot be used to advantage, which still is within the scope of aspects of the disclosed embodiments.

Claims

1. An inspection apparatus for inspecting a packaged cargo, the inspection apparatus comprising:

at least one conveyor configured to advance a packaged cargo through the inspection apparatus;

at least one camera arranged to capture bin image data of each bin load advanced through the inspection device using the at least one conveyor;

a processor operably coupled to the at least one conveyor and communicatively coupled to the at least one camera to receive the bin image data from the at least one camera,

wherein the processor is configured to characterize a box exterior protrusion of a box cargo from the box image data as a box flap in an open condition, wherein the processor is configured to parse the box image data and determine that the box exterior protrusion is a uniform flat surface, and is programmed with a parameter array of physical characteristic parameters describing a box flap uniformity attribute that determines the uniform flat surface defining an open box flap condition, and

Wherein the processor is configured to generate a physical property array from the box image data for each determined consistent planar surface and apply the parameter array to the physical property array to resolve the consistent planar surface into an open box flap.

2. An inspection apparatus according to claim 1, wherein the at least one camera is arranged to image each exposed bin side of each bin load advanced through the inspection apparatus with the at least one conveyor to image the bin exterior protrusion apparent on each imaged exposed bin side.

3. The inspection apparatus of claim 2, wherein the imaged exposed bin side is disposed such that the open bin flap resolved from the bin exterior protrusion apparent on the imaged exposed bin side extends from the exposed bin side adjacent a conveyor seating surface on which bin cargo sits.

4. An inspection apparatus according to claim 1, wherein the at least one camera is arranged to capture the bin image data of each exposed bin side of each bin load advanced through the inspection apparatus with the at least one conveyor such that the captured bin image data of each bin load embodies each exposed bin side outside the respective bin.

5. The inspection apparatus of claim 4, wherein the imaged exposed bin side is disposed such that the open bin flap resolved from the bin exterior protrusion apparent on the imaged exposed bin side extends from the exposed bin side adjacent a conveyor seating surface on which bin cargo sits.

6. An inspection apparatus according to claim 1, wherein the at least one camera is arranged to capture box image data of each box-packed good advanced through the inspection apparatus with the at least one conveyor such that the box image data embodies the box-external projections, wherein the box-external projections are apparent on at least one exposed box side, and the at least one exposed box side is disposed in each exposed box side orientation of a box-packed good.

7. The inspection apparatus of claim 6, wherein the at least one exposed bin side imaged by the at least one camera is disposed such that the open bin flap resolved from the bin exterior protrusion apparent on the imaged at least one exposed bin side extends from the at least one exposed bin side adjacent a conveyor seating surface on which bin cargo sits.

8. The inspection apparatus of claim 1, further comprising another imaging system separate and distinct from the at least one camera, wherein the other imaging system images different characteristics of the palletized load advanced through the inspection apparatus with the at least one conveyor, the different characteristics being distinct from the physical characteristics in the array of physical characteristics.

9. The inspection apparatus of claim 8, wherein the at least one camera captures bin image data substantially simultaneously with the other imaging system imaging the different characteristic of bin cargo.

10. The inspection apparatus of claim 1, further comprising another imaging system separate and distinct from the at least one camera, and the other imaging system images the palletized load, the imaging separate and distinct from the at least one camera imaging palletized load for inspection of palletized loads other than detection of the open bin flaps.

11. An inspection apparatus according to claim 10, wherein the further imaging system images the packaged goods for processor verification of the identity of each packaged good and the compliance of each packaged good with the verified package size parameter.

12. The inspection apparatus of claim 10, wherein the processor is configured such that a box cargo inspection based on a box cargo image from the other imaging system is parsed, the parsing being separate and distinct from parsing the open box flaps from the box image data of the at least one camera.

13. The inspection apparatus of claim 10, wherein the processor is configured to determine the presence of the bin exterior protrusion from imaging of the other imaging system separate and distinct from the bin image data captured with the at least one camera, and resolve the bin exterior protrusion from the bin image data of the at least one camera separate and distinct from the image of the other imaging system into an open bin flap.

14. The inspection apparatus of claim 10, wherein the processor is configured to determine the presence of the bin exterior protrusion from the bin image data captured by the at least one camera independent of an image of bin cargo captured by the other imaging system.

15. An inspection apparatus for inspecting a packaged cargo, the inspection apparatus comprising:

wherein the processor is configured to characterize a box exterior protrusion of a box cargo as an open box flap from the box image data, wherein the processor is configured to:

parsing the bin image data and determining that the bin exterior protrusion is a uniform flat surface, an

A physical property array of physical properties of the conforming planar surface is generated from the box image data for each determined conforming planar surface such that the physical property array describes the conforming planar surface as a box flap and determines that the box flap is in an open flap condition based on a parameter array of physical property parameters.

16. The inspection apparatus of claim 15 wherein the parameter set of physical characteristic parameters describes a box flap uniformity attribute that determines the uniform planar surface defining the open box flap condition.

17. A method for inspecting a packaged cargo, the method comprising:

utilizing at least one conveyor to advance the palletized load through the inspection apparatus;

utilizing at least one camera to capture bin image data of each bin load advanced through the inspection device utilizing the at least one conveyor;

providing a processor operably coupled to the at least one conveyor and communicatively coupled to the at least one camera to receive the bin image data from the at least one camera, and wherein the processor:

characterizing a box exterior protrusion of a box cargo from the box image data as a box flap in an open condition, wherein the processor is configured to parse the box image data and determine that the box exterior protrusion is a uniform planar surface, and is programmed with a parameter array of physical characteristic parameters describing a box flap uniformity attribute that determines the uniform planar surface defining an open box flap condition, an

Wherein the processor generates a physical property array from the box image data for each determined uniform flat surface and applies the parameter array to the physical property array to resolve the uniform flat surface into open box flaps.

18. A method according to claim 17, wherein the at least one camera is arranged to image each exposed bin side of each bin load advanced through the inspection apparatus using the at least one conveyor to image the bin exterior protrusions apparent on each imaged exposed bin side.

19. The method of claim 18, wherein the imaged exposed bin side is disposed such that the open bin flap resolved from the bin exterior protrusion apparent on the imaged exposed bin side extends from the exposed bin side adjacent a conveyor seating surface on which bin cargo sits.

20. A method according to claim 17, wherein the at least one camera is arranged to capture the bin image data of each exposed bin side of each bin load advanced through the inspection device using the at least one conveyor such that the captured bin image data of each bin load embodies each exposed bin side outside the respective bin.

21. The method of claim 20, wherein the imaged exposed bin side is disposed such that the open bin flap resolved from the bin exterior protrusion apparent on the imaged exposed bin side extends from the exposed bin side adjacent a conveyor seating surface on which bin cargo sits.

22. A method according to claim 17, wherein the at least one camera is arranged to capture box image data of each box cargo advanced through the inspection device with the at least one conveyor such that the box image data embodies the box exterior protrusion, wherein the box exterior protrusion is evident on at least one exposed box side, and the at least one exposed box side is disposed in each exposed box side orientation of box cargo.

23. The method of claim 22, wherein the at least one exposed bin side imaged by the at least one camera is disposed such that the open bin flap resolved from the bin exterior protrusion apparent on the imaged at least one exposed bin side extends from the at least one exposed bin side adjacent a conveyor seating surface on which bin cargo sits.

24. The method of claim 17, further comprising:

providing another imaging system separate and distinct from the at least one camera; and

using the further imaging system, different characteristics of the palletized load advanced through the inspection apparatus using the at least one conveyor are imaged, the different characteristics being different from the physical characteristics in the array of physical characteristics.

25. The method of claim 24, wherein the at least one camera captures bin image data substantially simultaneously with the other imaging system imaging the different characteristic of bin cargo.

26. The method of claim 17, further comprising:

imaging the palletized load with the further imaging system, the imaging being separate and distinct from the imaging of the at least one camera of palletized load for inspection of palletized loads other than the detection of the open bin flaps.

27. The method of claim 26, wherein the other imaging system images the packaged goods for processor verification of the identity of each packaged good and the compliance of each packaged good with the verified package size parameter.

28. The method of claim 26, wherein the processor is configured such that a box cargo inspection based on a box cargo image from the other imaging system is parsed, the parsing being separate and distinct from parsing the open box flaps from the box image data of the at least one camera.

29. The method of claim 26, wherein the processor is configured to determine the presence of the bin exterior protrusion from imaging of the other imaging system separate and distinct from the bin image data captured with the at least one camera, and resolve the bin exterior protrusion from the bin image data of the at least one camera separate and distinct from the image of the other imaging system into an open bin flap.

30. The method of claim 26, wherein the processor is configured to determine the presence of the bin exterior protrusion from the bin image data captured by the at least one camera independent of an image of bin cargo captured by the other imaging system.

31. A method for inspecting a packaged cargo, the method comprising:

Characterizing box exterior protrusions of box-packed goods as open box flaps from the box image data;

parsing the bin image data and determining that the bin exterior protrusion is a uniform flat surface; and

32. The method of claim 31 wherein the parameter array of physical characteristic parameters describes a box flap uniformity attribute that determines the uniform planar surface defining the open box flap condition.

33. An inspection apparatus for inspecting a packaged cargo, the inspection apparatus comprising:

a processor operably coupled to the at least one conveyor and communicatively coupled to the at least one camera to receive the bin image data from the at least one camera; and

Wherein the processor is configured to characterize at least one of a bin side recess and a bin exterior protrusion of the bin load as a bin flap in an open condition from the bin image data generated from a common image of the bin load captured by the at least one camera.

34. The inspection apparatus of claim 33, wherein the processor is configured to parse the bin image data and determine that the bin exterior protrusion is a uniform flat surface, and is programmed with a parameter array of physical characteristic parameters describing bin flap uniformity attributes that determine the uniform flat surface defining an open bin flap condition.

35. The inspection apparatus of claim 34, wherein the processor is configured to generate a physical property array from the bin image data for each determined consistent planar surface and apply the parameter array to the physical property array to resolve the consistent planar surface into open bin flaps.

36. An inspection apparatus according to claim 33, wherein the at least one camera is arranged to image each exposed bin side of each bin load advanced through the apparatus with the at least one conveyor to image at least one of the bin side recess and the bin exterior protrusion apparent on each imaged bin side from the common image of each imaged bin side.

37. An inspection apparatus according to claim 33, wherein the at least one camera is arranged to capture box image data of each box cargo advanced through the inspection apparatus with the at least one conveyor such that the box image data embodies at least one of the box side recesses and the box exterior protrusions, wherein at least one of the box side recesses and the box exterior protrusions is evident on at least one exposed box side and the at least one exposed box side is disposed in each exposed box side orientation of a box cargo.

38. The inspection apparatus of claim 37, wherein the at least one exposed bin side imaged by the at least one camera is disposed such that at least one of the bin side recess and the bin flap in an open condition, resolved from at least one of the bin side recess and the bin exterior protrusion apparent on the at least one exposed bin side, extends from the at least one exposed bin side adjacent a conveyor seating surface on which bin cargo sits.

39. The inspection apparatus of claim 33, further comprising another imaging system separate and distinct from the at least one camera, and the other imaging system images the packaged goods, the imaging separate and distinct from the at least one camera imaging the packaged goods for inspection of packaged goods other than detection of at least one of the box-side recess and the open box flap.

40. An inspection apparatus according to claim 39, wherein the further imaging system images the packaged goods for processor verification of the identity of each packaged good and the compliance of each packaged good with the verified package size parameter.

41. The inspection apparatus of claim 39, wherein the processor is configured such that a box cargo inspection based on a box cargo image from the other imaging system is parsed, the parsing being separate and distinct from parsing at least one of the box side recess and the open box flap from the box image data of the at least one camera.

42. The inspection apparatus of claim 39, wherein the processor is configured to determine the presence of at least one of the bin-side recess and the bin-exterior protrusion of bin cargo from imaging of the other imaging system separate and distinct from the bin-image data captured with the at least one camera, and parse the at least one of the bin-side recess and the bin-exterior protrusion into respective bin recesses and open bin flaps from the bin-image data of the at least one camera separate and distinct from the image of the other imaging system.

43. The inspection apparatus of claim 39, wherein the processor is configured to determine the presence of at least one of the bin-side recess and the bin-exterior protrusion on a bin-cargo side from the bin image data captured by the at least one camera independent of an image of the bin-cargo captured by the other imaging system.

44. An inspection apparatus for inspecting a packaged cargo, the inspection apparatus comprising:

wherein:

the processor is configured to characterize at least one bin top or at least one bin side having a dishing condition from the bin image data of bin cargo captured by the at least one camera, wherein the processor is programmed to resolve from the image data an inward shift of a predetermined planar uniformity characteristic of the at least one bin top or the at least one bin side with the bin top or bin side; and

The processor is configured to determine, from the image data, a physical characteristic describing a dishing condition of the at least one bin top or the at least one bin side for each resolved inwardly varying presence.

45. The inspection apparatus of claim 44, wherein the processor is configured to parse the bin image data and determine that the at least one bin top or the at least one bin side has an inward variation, and is programmed with a parameter array of physical characteristic parameters describing an inward variation attribute that determines the inward variation defining a dishing condition.

46. The inspection apparatus of claim 45, wherein the processor is configured to generate a physical property array from the bin image data for each determined inward variation and apply the parameter array to the physical property array to resolve the inward variation to a dishing condition.

47. An inspection apparatus according to claim 44, wherein the at least one camera is arranged to image each exposed bin side of each bin load advanced through the inspection apparatus using the at least one conveyor to image a dishing condition apparent on each imaged bin side from the common image of each imaged bin side.

48. The inspection apparatus of claim 44, wherein the at least one camera is arranged to capture box image data of each box cargo advanced through the inspection apparatus with the at least one conveyor such that the box image data embodies a recessed condition, wherein the recessed condition is evident on at least one exposed box side, and the at least one exposed box side is disposed in each exposed box side orientation of a box cargo.

49. The inspection apparatus of claim 44, further comprising another imaging system separate and distinct from the at least one camera, and the other imaging system images the packaged goods, the imaging separate and distinct from the at least one camera imaging the packaged goods for inspection of the packaged goods other than detection of the dent condition.

50. An inbound conveyor system for guiding containerized goods in a logistics facility, the system comprising: at least one conveyor configured to push box-packed cargo into the logistics facility;

a bin inspection station arranged to communicate with the at least one conveyor such that bin contents advance through the bin inspection station, the bin inspection station having at least one bin inspection camera configured to capture an image of a shadow of each bin contents advanced through the bin inspection station;

At least one further camera connected to the bin inspection station, separate and distinct from the at least one bin inspection camera, and arranged to capture other bin image data of each bin load advanced through the bin inspection station in addition to the bin image data captured by the at least one bin inspection camera; and

a processor operatively coupled to the at least one conveyor, communicatively coupled to the at least one bin inspection camera, to receive the bin image data from the at least one bin inspection camera, and communicatively coupled to the at least another camera, to receive the other bin image data for each bin load from the at least another camera, wherein the processor is configured to determine predetermined characteristics of each bin load that determine a bin form from the image of the shadow of each bin load imaged by the at least one bin inspection camera, thereby confirming that the respective bin load has a bin shape, and wherein the processor is configured to determine compliance of the respective bin load with the predetermined bin form fit characteristics from the other image data after confirming that the respective bin load has the bin form.

51. The inbound conveyor system of claim 50, wherein the predetermined bin form fit characteristics inform of the assembly acceptance of the respective bin load within a predetermined assembly space or location of a storage array of the logistics facility.

52. The inbound conveyor system of claim 51, wherein the predetermined assembly space or location is a pallet load build location in a pallet build formed in the logistics facility.

53. The inbound conveyor system of claim 50, wherein the predetermined bin form adaptation characteristic is an inward protrusion or depression of at least one side of the bin shape of the respective bin load relative to a flat bin side.

54. The inbound conveyor system of claim 50, wherein the predetermined characteristics that determine each palletized load in bin form include one or more of bin length, bin width, bin height, included angle between bin sides, and bin size.

55. The inbound conveyor system of claim 50, wherein the processor comprises:

an image acquisition assembly configured to acquire more than one digitized image from the bin inspection station for each bin load advanced through the bin inspection station; and

An image combiner configured to selectively combine a plurality of acquired digitized images other than the more than one digitized image into a combined image based on a continuous input beam spatial intensity reduction below a first threshold for a duration of the more than one of the acquired digitized images.

56. The inbound conveyor system of claim 55, wherein the processor is configured to identify the presence of a translucent shrink wrap disposed on a product in the box cargo based on a continuous input beam spatial intensity decrease below a second threshold to confirm the presence of the box cargo.

57. The inbound conveyor system of claim 56, wherein the image combiner is configured to selectively combine the acquired digitized images into a potential product combination image, wherein a plurality of pixels digitized in the image having a reduced intensity below a first predetermined threshold define an image width greater than a second threshold.

58. The inbound conveyor system of claim 56, wherein the image combiner is configured to selectively combine the acquired digitized images to form the combined image, wherein a predetermined combined image length is represented across a plurality of pixels digitized with decreasing intensities below a first predetermined threshold and a second threshold.

59. The inbound conveyor system of claim 55, wherein the at least one conveyor is configured to advance the containerized good at an advancement rate, the image acquisition assembly being configured to acquire the digitized image at an acquisition rate that is proportional to the advancement rate of the containerized good.

60. The inbound conveyor system of claim 59, wherein the image acquisition rate is synchronized through the use of an encoder or through stepper motor drive circuitry.

61. The inbound conveyor system of claim 55, wherein the image acquisition component comprises an image cache.

62. The inbound conveyor system of claim 55, wherein the at least one bin inspection camera is configured to determine ambient light intensity from a sample buffer of cached images.

63. The inbound conveyor system of claim 55, wherein the processor is configured to determine a size from the combined image of: a first shape best fit in the combined image, a second shape bounding the combined image, and a difference between the first shape and the second shape.

64. The inbound conveyor system of claim 55, wherein the processor is configured to determine an orientation angle of the palletized load with respect to the at least one conveyor from the combined image.

65. The inbound conveyor system of claim 55, wherein the processor is configured to determine a distance of the palletized load from one side of the at least one conveyor from the combined image.

66. The inbound conveyor system of claim 50, wherein the bin inspection station is configured to identify the presence of debris on an input window of the at least one bin inspection camera based on common pixels of the same intensity across a plurality of digitized images.

67. A method in an inspection apparatus for inspecting a packaged cargo, the method comprising:

utilizing at least one camera to capture bin image data of each bin load advanced through the inspection device utilizing the at least one conveyor; and

providing a processor and utilizing the processor to receive the box image data from the at least one camera, wherein

The processor is operably coupled to the at least one conveyor and communicatively coupled to the at least one camera, and

the processor is configured to characterize at least one of a bin side recess and a bin exterior protrusion of the bin load as a bin flap in an open condition from the bin image data generated from a common image of the bin load captured by the at least one camera.

68. The method of claim 67 wherein the processor parses the bin image data and determines that the bin exterior protrusion is a uniform flat surface, the processor programmed with a parameter array of physical characteristic parameters describing bin flap uniformity attributes that determine the uniform flat surface defining an open bin flap condition.

69. The method of claim 67 wherein the at least one camera is arranged to image each exposed bin side of each bin load propelled through the apparatus with the at least one conveyor to image at least one of the bin side recesses and the bin exterior protrusions apparent on each imaged bin side from the common image of each imaged bin side.

70. The method of claim 67 wherein the at least one camera is arranged to capture box image data of each box cargo advanced through the inspection device with the at least one conveyor such that the box image data embodies at least one of the box side recesses and the box exterior protrusions, wherein the at least one of the box side recesses and the box exterior protrusions is evident on at least one exposed box side and the at least one exposed box side is disposed in each exposed box side orientation of the box cargo.

71. The method of claim 67 further comprising imaging the palletized load with another imaging system separate and distinct from the at least one camera, the imaging separate and distinct from imaging the at least one camera of palletized load for inspection of palletized loads other than detection of at least one of the box side recess and the open box flap.